diff --git a/404.html b/404.html index 6eca903..3e2a2db 100644 --- a/404.html +++ b/404.html @@ -24,7 +24,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/LICENSE-text.html b/LICENSE-text.html index 442fc01..7b0701a 100644 --- a/LICENSE-text.html +++ b/LICENSE-text.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/authors.html b/authors.html index abeba10..a5df51d 100644 --- a/authors.html +++ b/authors.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/index.html b/index.html index e50d9c0..1e06cfc 100644 --- a/index.html +++ b/index.html @@ -30,7 +30,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/news/index.html b/news/index.html index e43765a..582cfc6 100644 --- a/news/index.html +++ b/news/index.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 @@ -44,6 +44,11 @@ Source: NEWS.md + +DAISIEutils 1.6.2 +Prevent parameter values above upper bound being passed to the relaxed rate model in run_daisie_ml() (#34). +Lower the value given as initial parameter value when estimated as infinite for the relaxed rate model in run_daisie_ml(). + DAISIEutils 1.6.1 Migrate from now defunct Peregrine HPCC to the new Hábrók HPCC diff --git a/pkgdown.yml b/pkgdown.yml index ad03812..121619b 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -2,7 +2,7 @@ pandoc: 2.19.2 pkgdown: 2.0.7 pkgdown_sha: ~ articles: {} -last_built: 2023-10-20T09:15Z +last_built: 2023-10-20T09:23Z urls: reference: https://tece-lab.github.io/DAISIEutils/reference article: https://tece-lab.github.io/DAISIEutils/articles diff --git a/reference/Azores.html b/reference/Azores.html index 3bcbd10..16d56eb 100644 --- a/reference/Azores.html +++ b/reference/Azores.html @@ -18,7 +18,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/Azores_alt_m.html b/reference/Azores_alt_m.html index e045323..25db4bb 100644 --- a/reference/Azores_alt_m.html +++ b/reference/Azores_alt_m.html @@ -18,7 +18,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/DAISIEutils-package.html b/reference/DAISIEutils-package.html index 6768553..62b7d65 100644 --- a/reference/DAISIEutils-package.html +++ b/reference/DAISIEutils-package.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/bootstrap.html b/reference/bootstrap.html index bce3596..aa01746 100644 --- a/reference/bootstrap.html +++ b/reference/bootstrap.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/bootstrap_lr.html b/reference/bootstrap_lr.html index 5358bc1..7fcea00 100644 --- a/reference/bootstrap_lr.html +++ b/reference/bootstrap_lr.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/calc_bic.html b/reference/calc_bic.html index e4e5f5d..8852fce 100644 --- a/reference/calc_bic.html +++ b/reference/calc_bic.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/calc_loglik_ratio.html b/reference/calc_loglik_ratio.html index d3a5d5e..aa51721 100644 --- a/reference/calc_loglik_ratio.html +++ b/reference/calc_loglik_ratio.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/calc_p_value.html b/reference/calc_p_value.html index 7325bc8..a11c593 100644 --- a/reference/calc_p_value.html +++ b/reference/calc_p_value.html @@ -14,7 +14,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/calc_power.html b/reference/calc_power.html index f05f43a..b09c110 100644 --- a/reference/calc_power.html +++ b/reference/calc_power.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/calc_sim_metrics.html b/reference/calc_sim_metrics.html index 1456f54..21b0d22 100644 --- a/reference/calc_sim_metrics.html +++ b/reference/calc_sim_metrics.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/check_rep_seeds.html b/reference/check_rep_seeds.html index fc61456..aef4be8 100644 --- a/reference/check_rep_seeds.html +++ b/reference/check_rep_seeds.html @@ -12,7 +12,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/check_rep_seeds_depr.html b/reference/check_rep_seeds_depr.html index ab0edc3..4fb2a52 100644 --- a/reference/check_rep_seeds_depr.html +++ b/reference/check_rep_seeds_depr.html @@ -12,7 +12,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/choose_best_model.html b/reference/choose_best_model.html index d880535..ac4304c 100644 --- a/reference/choose_best_model.html +++ b/reference/choose_best_model.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/create_output_folder.html b/reference/create_output_folder.html index e9ad829..69aad11 100644 --- a/reference/create_output_folder.html +++ b/reference/create_output_folder.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/create_results_dir_path.html b/reference/create_results_dir_path.html index a38ea73..3158bc0 100644 --- a/reference/create_results_dir_path.html +++ b/reference/create_results_dir_path.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/default_params_doc.html b/reference/default_params_doc.html index 2b64da3..15406f9 100644 --- a/reference/default_params_doc.html +++ b/reference/default_params_doc.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/get_available_models.html b/reference/get_available_models.html index 0e5e9c6..3fd6a46 100644 --- a/reference/get_available_models.html +++ b/reference/get_available_models.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/index.html b/reference/index.html index 285899a..b36eb17 100644 --- a/reference/index.html +++ b/reference/index.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/is_on_cluster.html b/reference/is_on_cluster.html index b7ac063..f5b20ab 100644 --- a/reference/is_on_cluster.html +++ b/reference/is_on_cluster.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/plot_bootstrap_results.html b/reference/plot_bootstrap_results.html index 1f8eaa1..80d260d 100644 --- a/reference/plot_bootstrap_results.html +++ b/reference/plot_bootstrap_results.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/plot_sim_metrics.html b/reference/plot_sim_metrics.html index 0007ccf..61de896 100644 --- a/reference/plot_sim_metrics.html +++ b/reference/plot_sim_metrics.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/print_metadata.html b/reference/print_metadata.html index 33ae242..e5284ef 100644 --- a/reference/print_metadata.html +++ b/reference/print_metadata.html @@ -12,7 +12,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/read_model_results.html b/reference/read_model_results.html index 2e3fb5c..f499903 100644 --- a/reference/read_model_results.html +++ b/reference/read_model_results.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/run_daisie_2type_ml.html b/reference/run_daisie_2type_ml.html index 60a869c..34bc511 100644 --- a/reference/run_daisie_2type_ml.html +++ b/reference/run_daisie_2type_ml.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/run_daisie_ml.html b/reference/run_daisie_ml.html index bf9a568..56b8ba5 100644 --- a/reference/run_daisie_ml.html +++ b/reference/run_daisie_ml.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/run_sim.html b/reference/run_sim.html index 38164f7..3393205 100644 --- a/reference/run_sim.html +++ b/reference/run_sim.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/sensitivity.html b/reference/sensitivity.html index f367ddd..efa8885 100644 --- a/reference/sensitivity.html +++ b/reference/sensitivity.html @@ -18,7 +18,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/setup_2type_model.html b/reference/setup_2type_model.html index e4202e6..9a22870 100644 --- a/reference/setup_2type_model.html +++ b/reference/setup_2type_model.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 @@ -172,7 +172,7 @@ Examples#> #> $initparsopt #> lac mu k gam laa -#> 0.95829023 0.81521667 186.44782309 0.09438888 1.17948246 +#> 1.440610e+00 1.377048e+00 1.680143e+02 1.734061e-03 1.513600e+00 #> #> $cs_version #> [1] 1 diff --git a/reference/setup_model.html b/reference/setup_model.html index 721598e..3c79666 100644 --- a/reference/setup_model.html +++ b/reference/setup_model.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 @@ -174,7 +174,7 @@ Examples#> #> $initparsopt #> lac mu k gam laa -#> 1.49976301 1.60932627 148.16579102 0.09281851 0.65453359 +#> 0.63644094 0.48772227 186.99077689 0.08761113 3.41426549 #> #> $cs_version #> [1] 1 diff --git a/reference/setup_std_pars2.html b/reference/setup_std_pars2.html index 7d2f136..1072360 100644 --- a/reference/setup_std_pars2.html +++ b/reference/setup_std_pars2.html @@ -26,7 +26,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/reference/summarize_bootstrap_results.html b/reference/summarize_bootstrap_results.html index b374474..221796f 100644 --- a/reference/summarize_bootstrap_results.html +++ b/reference/summarize_bootstrap_results.html @@ -10,7 +10,7 @@ DAISIEutils - 1.6.1 + 1.6.2 diff --git a/search.json b/search.json index 0ef12e6..741b4f5 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://tece-lab.github.io/DAISIEutils/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Pedro Santos Neves. Author, maintainer. Joshua W. Lambert. Author. Luis Valente. Author. Richèl J.C. Bilderbeek. Author. Rampal S. Etienne. Author.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Santos Neves P, Lambert J, Valente L, Bilderbeek R, Etienne R (2023). DAISIEutils: Utility Functions DAISIE Package. https://github.com/tece-lab/DAISIEutils, https://tece-lab.github.io/DAISIEutils/.","code":"@Manual{, title = {DAISIEutils: Utility Functions for the DAISIE Package}, author = {Pedro {Santos Neves} and Joshua W. Lambert and Luis Valente and Richèl J.C. Bilderbeek and Rampal S. Etienne}, year = {2023}, note = {https://github.com/tece-lab/DAISIEutils, https://tece-lab.github.io/DAISIEutils/}, }"},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"daisieutils","dir":"","previous_headings":"","what":"Utility Functions for the DAISIE Package","title":"Utility Functions for the DAISIE Package","text":"goal DAISIEutils collect useful utility functions used recurrently DAISIE projects. DAISIEutils companion package R package DAISIE. includes pipelines typical analyses using DAISIE’s maximum likelihood inference. Note: DAISIEutils depends latest CRAN release DAISIE. used older versions DAISIE package.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Utility Functions for the DAISIE Package","text":"can install released version DAISIEutils GitHub :","code":"install.packages(\"remotes\") remotes::install_github(\"tece-lab/DAISIEutils\")"},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"features","dir":"","previous_headings":"","what":"Features","title":"Utility Functions for the DAISIE Package","text":"DAISIEutils allows researcher easily accomplish following tasks: Choose specify number common DAISIE models, different combinations free initial parameters. Fit said models data, sampling number initial parameters minimize model convergence local optima. Choose best fitting models. Run bootstrap likelihood ratio tests. Test sensitivity results changing data sets.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"supportquestions","dir":"","previous_headings":"","what":"Support/Questions","title":"Utility Functions for the DAISIE Package","text":"feature requests bug-reports, please submit issue. matters, contact authors: @Neves-P @joshwlambert.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":null,"dir":"Reference","previous_headings":"","what":"Birds of Azores archipelago — Azores","title":"Birds of Azores archipelago — Azores","text":"dataset containing age archipelago, number species mainland present island, colonising clade colonisation branching times, endemicity status, missing species, type species. Obtained parsed relaxedDAISIE project strictly illustration test purposes","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Birds of Azores archipelago — Azores","text":"","code":"Azores"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Birds of Azores archipelago — Azores","text":"object class list length 18: island_age Age island not_present Number mainland species colonise island colonist_name name colonising clade branching_times age island colonisation subsequent branching times clade stac Endemicity status clade missing_species Number species missing phylogeny clade type1or2 Defines type species clade, used 2-type analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Birds of Azores archipelago — Azores","text":"Valente et al. (2020) doi: https://doi.org/10.1038/s41586-020-2022-5 https://github.com/joshwlambert/relaxedDAISIE","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":null,"dir":"Reference","previous_headings":"","what":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"dataset containing age archipelago, number species mainland present island, colonising clade colonisation branching times, endemicity status, missing species, type species. Obtained parsed relaxedDAISIE project strictly illustration test purposes","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"","code":"Azores_alt_m"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"object class list length 18: island_age Age island not_present Number mainland species colonise island colonist_name name colonising clade branching_times age island colonisation subsequent branching times clade stac Endemicity status clade missing_species Number species missing phylogeny clade type1or2 Defines type species clade, used 2-type analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"Valente et al. (2020) doi: https://doi.org/10.1038/s41586-020-2022-5 https://github.com/joshwlambert/relaxedDAISIE","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/DAISIEutils-package.html","id":null,"dir":"Reference","previous_headings":"","what":"DAISIEutils: Utility Functions for the DAISIE Package — DAISIEutils-package","title":"DAISIEutils: Utility Functions for the DAISIE Package — DAISIEutils-package","text":"goal DAISIEutils collect useful utility functions used recurently DAISIE projects. DAISIEutils companion package R package DAISIE.","code":""},{"path":[]},{"path":"https://tece-lab.github.io/DAISIEutils/reference/DAISIEutils-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"DAISIEutils: Utility Functions for the DAISIE Package — DAISIEutils-package","text":"Maintainer: Pedro Santos Neves p.m.santos.neves@rug.nl (ORCID) Authors: Joshua W. Lambert j.w.l.lambert@rug.nl (ORCID) Luis Valente luis.valente@naturalis.nl (ORCID) Richèl J.C. Bilderbeek richel@richelbilderbeek.nl (ORCID) Rampal S. Etienne r.s.etienne@rug.nl (ORCID)","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":null,"dir":"Reference","previous_headings":"","what":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"Runs bootstrapping DAISIE model determine parameter precision","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"","code":"bootstrap( daisie_data, data_name, model, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"Nothing. Writes bootstrapping results .rds file. file stored $HOME/results/data_name running cluster /results/data_name running locally. directory created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") bootstrap( daisie_data = Galapagos_datalist, data_name = \"Galapagos_datalist\", model = \"cr_dd\", array_index = 1, cond = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":null,"dir":"Reference","previous_headings":"","what":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"Runs parameteric bootstrapping likelihood ratio test two DAISIE models","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"","code":"bootstrap_lr( daisie_data, data_name, model_1, model_2, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model_1 string model run. list options see documentation model parameter run_daisie_ml(). model_2 string model run. list options see documentation model parameter run_daisie_ml(). array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"Nothing. Writes bootstrapping results .rds file. file stored file_path. directory file_path created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") bootstrap_lr( daisie_data = Galapagos_datalist, model_1 = \"cr_dd\", model_2 = \"cr_di\", array_index = 1, cond = 1, ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Bayesian Information Criterion of a model — calc_bic","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"Compute Bayesian Information Criterion model","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"","code":"calc_bic(results, daisie_data)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"results data frame containing model results created run_daisie_ml(). results DAISIE::DAISIE_ML_CS() bic, saved RDS file run_daisie_ml(). daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"Numeric value BIC","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"Joshua W. Lambert, Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"Calculates loglikelihood ratio two models","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"","code":"calc_loglik_ratio(model_1_lik_res, model_2_lik_res)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"model_1_lik_res data frame results DAISIE maximum likelihood model. model_2_lik_res data frame results DAISIE maximum likelihood model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"Numeric likelihood ratio","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"Calculates p-value rejecting model distribution likelihood ratios","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"","code":"calc_p_value(daisie_data, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"Numeric p-value","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates power to detect the true model — calc_power","title":"Calculates power to detect the true model — calc_power","text":"Calculates power detect true model","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates power to detect the true model — calc_power","text":"","code":"calc_power(daisie_data, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates power to detect the true model — calc_power","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates power to detect the true model — calc_power","text":"Numeric power","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates summary metrics from a simulation — calc_sim_metrics","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"Calculates summary metrics simulation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"","code":"calc_sim_metrics(daisie_data)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"List simulation metrics","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks if jobs were run with the same seed — check_rep_seeds","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"Checks every log file inside folder record used seed. Returns duplicated seeds corresponding job arrays.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"","code":"check_rep_seeds(logs_path)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"logs_path Character path folder containing logs. log files present, plain text format.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"data frame four columns. line contains information one result duplicated seed. lines duplicated seeds logs. Columns follows: Data: character vector name data set duplicates found. Models: numeric corresponding array index. empty duplicates found. Seeds: numeric corresponding seed duplicated. Array_indices: numeric corresponding array index.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"function preferred method checking presence repeated seeds. However, fail log files generated older versions package, expects seed array information always location. encounter issues, try running check_rep_seeds_depr() instead. cases, give preference function better optimization log output parsing possible.","code":""},{"path":[]},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"","code":"if (FALSE) { repeated_seeds <- check_rep_seeds(logs_path = \"/logs/\") }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"Checks every log file inside folder record used seed returns duplicated seeds corresponding job arrays.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"","code":"check_rep_seeds_depr(logs_path)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"logs_path Character path folder containing logs. log files present, plain text format.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"data frame four columns. line contains information one result duplicated seed. lines duplicated seeds logs. Columns follows: Data: character vector name data set duplicates found. Models: numeric corresponding array index. empty duplicates found. Seeds: numeric corresponding seed duplicated. Array_indices: numeric corresponding array index.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"function, lines containing scraped values can anywhere file, occurred older versions package. Checking thus less efficient preference given check_rep_seeds() cases, unless older log files checked. check_rep_seeds() fail older log files.","code":""},{"path":[]},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"","code":"if (FALSE) { repeated_seeds <- check_rep_seeds_depr(logs_path = \"/logs/\") }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":null,"dir":"Reference","previous_headings":"","what":"From multiple seeds, choose the best model fit — choose_best_model","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"multiple seeds, choose best model fit","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"","code":"choose_best_model(model_lik_res)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"model_lik_res data frame results DAISIE maximum likelihood model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"list length one, data frame 1 row containing best estimated models given seeds, determined loglik. model estimated successfully, returns similar structure fields NA.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":null,"dir":"Reference","previous_headings":"","what":"Create output folder — create_output_folder","title":"Create output folder — create_output_folder","text":"Create output folder","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create output folder — create_output_folder","text":"","code":"create_output_folder(data_name, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create output folder — create_output_folder","text":"data_name String. used name created output folder. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create output folder — create_output_folder","text":"Creates appropriate directory. Returns string path output object. default, Hábrók, folder $HOME/results/$data_name. called another environment, folder getwd()/results/$data_name. Alternatively, another valid root can specified, resulting results_dir/$data_name.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create output folder — create_output_folder","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create output folder — create_output_folder","text":"","code":"if (FALSE) { create_output_folder( data_name = \"results_folder\" ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":null,"dir":"Reference","previous_headings":"","what":"Create results directory path — create_results_dir_path","title":"Create results directory path — create_results_dir_path","text":"Create results directory path","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create results directory path — create_results_dir_path","text":"","code":"create_results_dir_path(data_name, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create results directory path — create_results_dir_path","text":"data_name String. used name created output folder. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create results directory path — create_results_dir_path","text":"String platform appropriate file path used results directory given data set.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create results directory path — create_results_dir_path","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create results directory path — create_results_dir_path","text":"","code":"results_dir_path <- create_results_dir_path(data_name = \"Azores\")"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":null,"dir":"Reference","previous_headings":"","what":"Default parameters documentation — default_params_doc","title":"Default parameters documentation — default_params_doc","text":"Default parameters documentation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default parameters documentation — default_params_doc","text":"","code":"default_params_doc( model, data_name, results_root_folder, daisie_data, array_index, file_path, results, cond, optimmethod, methode, model_1, model_2, model_1_lik_res, model_2_lik_res, model_lik_res, lik_res, data_names, full_output, seed, test, logs_path, results_dir, overall_results, sumstats, ylim4, title, ddmodel, verbose, island_ontogeny, eqmodel, tol, maxiter, x_E, x_I, mainland_n, low_rates, rep_index, res, prop_type2_pool, par_upper_bound )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default parameters documentation — default_params_doc","text":"model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free data_name String. used name created output folder. results_root_folder Character. path root folder containing subfolders. subfolder contains result files analysis runs. daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. array_index single numeric array index. used naming output file. file_path system directory output files stored. results data frame containing model results created run_daisie_ml(). results DAISIE::DAISIE_ML_CS() bic, saved RDS file run_daisie_ml(). cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). model_1 string model run. list options see documentation model parameter run_daisie_ml(). model_2 string model run. list options see documentation model parameter run_daisie_ml(). model_1_lik_res data frame results DAISIE maximum likelihood model. model_2_lik_res data frame results DAISIE maximum likelihood model. model_lik_res data frame results DAISIE maximum likelihood model. lik_res data frame results DAISIE maximum likelihood model. data_names vector strings names data sets want compare sensitivity. full_output boolean determining whether full model output returned. seed Integer value used seed Mersenne-Twister. value determined Sys.time() array_index ensure parallel jobs different seeds. last 6 digits Sys.time() (integer) used. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed. logs_path Character path folder containing logs. log files present, plain text format. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. overall_results summary results obtained summarize_bootstrap_results(). sumstats vector number species, number colonization, size largest clade rank largest clade empirical data ylim4 maximum plot rank largest clade. title title plot. ddmodel Sets model diversity-dependence: ddmodel = 0: diversity dependence ddmodel = 1: linear dependence speciation rate ddmodel = 11: linear dependence speciation rate immigration rate ddmodel = 2: exponential dependence speciation rate ddmodel = 21: exponential dependence speciation rate immigration rate verbose simulation dataprep functions logical, Default = TRUE gives intermediate output printed. ML functions numeric determining intermediate output printed, Default = 0 print, verbose = 1 prints intermediate output parameters loglikelihood, verbose = 2 means also intermediate progress loglikelihood computation shown. island_ontogeny DAISIE_sim_time_dep(), DAISIE_ML_CS plotting string describing type island ontogeny. Can \"const\", \"beta\" beta function describing area time. functions numeric describing type island ontogeny. Can 0 constant, 1 beta function describing area time. ML functions island_ontogeny = NA assumes constant ontogeny. Time dependent estimation yet available development still ongoing. return error called case. eqmodel Sets equilibrium constraint can used likelihood optimization. available datatype = 'single'. eqmodel = 0 : equilibrium assumed eqmodel = 13 : near-equilibrium assumed endemics using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value eqmodel = 15 : near-equilibrium assumed endemics immigrants using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value, non-endemics must within x_I equilibrium value. tol Sets tolerances optimization. Consists : reltolx - relative tolerance parameter values optimization. reltolf - relative tolerance function value optimization. abstolx - absolute tolerance parameter values optimization. maxiter Sets maximum number iterations optimization. x_E Sets fraction equlibrium endemic diversity endemics assumed equilibrium; active eqmodel = 13 15. x_I Sets fraction equlibrium non-endemic diversity system assumed equilibrium; active eqmodel = 15. mainland_n numeric stating number mainland species, number species can potentially colonize island. using clade-specific diversity dependence, value set 1 internally simulation. using island-wide diversity dependence, value set number mainland species. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. rep_index string default \"NULL\" (string true NULL due passed command line), can string numeric used detect whether multiple data set data source run. case, example, fitting DAISIE model posterior distribution data. res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. prop_type2_pool numeric determining proportion mainland species pool composed type 2 species. par_upper_bound numeric defining upper limit integration parameter fitting relaxed-rate DAISIE model. DAISIE model applied relaxed-rate model, parameter can ignored left default influence model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default parameters documentation — default_params_doc","text":"Nothing","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":null,"dir":"Reference","previous_headings":"","what":"List all available models — get_available_models","title":"List all available models — get_available_models","text":"List available models","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List all available models — get_available_models","text":"","code":"get_available_models()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List all available models — get_available_models","text":"character vector named codes available models.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"List all available models — get_available_models","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List all available models — get_available_models","text":"","code":"available_models <- DAISIEutils:::get_available_models()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if code is running on Hábrók HPCC — is_on_cluster","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"Check code running Hábrók HPCC","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"","code":"is_on_cluster()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"Boolean. TRUE called Hábrók HPCC, FALSE .","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"","code":"on_cluster <- is_on_cluster()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"output list results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"","code":"plot_bootstrap_results( overall_results, sumstats = c(65, 5, 28, 1), ylim4 = 0.7, title = NULL )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"overall_results summary results obtained summarize_bootstrap_results(). sumstats vector number species, number colonization, size largest clade rank largest clade empirical data ylim4 maximum plot rank largest clade. title title plot.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"Rampal S. Etienne & Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"","code":"if (FALSE) { clado_rate <- 0.5 ext_rate <- 0.2 carr_cap <- Inf immig_rate <- 0.005 ana_rate <- 1 sim_pars <- c(clado_rate, ext_rate, carr_cap, immig_rate, ana_rate) set.seed(1) dataset_cs <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"CS\" ) dataset_iw <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"IW\" ) overall_results_cs <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_cs ) overall_results_iw <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_iw ) par(mfrow = c(2, 4), cex.lab = 1.5, cex.main = 1.5) DAISIEutils::plot_bootstrap_results( overall_results = overall_results_cs, title = \"Simulated under CS\" ) DAISIEutils::plot_bootstrap_results( overall_results = overall_results_iw, title = \"Simulated under IW\" ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots metrics from simulations — plot_sim_metrics","title":"Plots metrics from simulations — plot_sim_metrics","text":"Plots metrics simulations","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots metrics from simulations — plot_sim_metrics","text":"","code":"plot_sim_metrics(sim_metrics)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots metrics from simulations — plot_sim_metrics","text":"sim_metrics list metrics output calc_sim_metrics()","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots metrics from simulations — plot_sim_metrics","text":"none Four plots shown: histogram number species, histogram number colonizations, histogram largest clade size histogram rank largest clade","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plots metrics from simulations — plot_sim_metrics","text":"Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Print session and run info to console/log file — print_metadata","title":"Print session and run info to console/log file — print_metadata","text":"Useful call start normal job scripts run cluster metadata recorded log files.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print session and run info to console/log file — print_metadata","text":"","code":"print_metadata(data_name, model, array_index, seed, methode, optimmethod)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print session and run info to console/log file — print_metadata","text":"data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. seed Integer value used seed Mersenne-Twister. value determined Sys.time() array_index ensure parallel jobs different seeds. last 6 digits Sys.time() (integer) used. methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print session and run info to console/log file — print_metadata","text":"Nothing. Prints session run info used DAISIE console.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Print session and run info to console/log file — print_metadata","text":"Message used print function arguments. retain formatting, simple sessioninfo::session_info() used session info, uses print. Hence, session_info() go stdout, remaining output function go stderr.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Print session and run info to console/log file — print_metadata","text":"Pedro Santos Neves, Luis Valente, Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print session and run info to console/log file — print_metadata","text":"","code":"if (FALSE) { print_metadata( data_name = \"Galapagos_datalist\", model = \"cr_di\", array_index = 1, seed = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Reads run_daisie_ml() results — read_model_results","title":"Reads run_daisie_ml() results — read_model_results","text":"Reads run_daisie_ml() results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reads run_daisie_ml() results — read_model_results","text":"","code":"read_model_results(results_root_folder)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Reads run_daisie_ml() results — read_model_results","text":"results_root_folder Character. path root folder containing subfolders. subfolder contains result files analysis runs.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Reads run_daisie_ml() results — read_model_results","text":"Nested list. First layer corresponds data sets, per folders found results_root_folder. second layer corresponds models run dataset, containing 1 row long data frame alternate seed runs model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Reads run_daisie_ml() results — read_model_results","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":null,"dir":"Reference","previous_headings":"","what":"Run 2 type DAISIE analysis — run_daisie_2type_ml","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"Run 2 type DAISIE analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"","code":"run_daisie_2type_ml( daisie_data, data_name, model, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, low_rates = FALSE, rep_index = \"NULL\", res = 100, prop_type2_pool, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. rep_index string default \"NULL\" (string true NULL due passed command line), can string numeric used detect whether multiple data set data source run. case, example, fitting DAISIE model posterior distribution data. res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. prop_type2_pool numeric determining proportion mainland species pool composed type 2 species. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"Nothing. Writes DAISIE analysis results .rds file. file stored file_path. directory file_path created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"Pedro Santos Neves, Joshua W. Lambert, Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") run_daisie_2type_ml( daisie_data = Galapagos_datalist, data_name = \"Galapagos_datalist\", model = \"cr_dd\", array_index = 1, cond = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":null,"dir":"Reference","previous_headings":"","what":"Run DAISIE analysis — run_daisie_ml","title":"Run DAISIE analysis — run_daisie_ml","text":"Run DAISIE analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run DAISIE analysis — run_daisie_ml","text":"","code":"run_daisie_ml( daisie_data, data_name, model, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, low_rates = FALSE, rep_index = \"NULL\", res = 100, par_upper_bound = Inf, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run DAISIE analysis — run_daisie_ml","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. rep_index string default \"NULL\" (string true NULL due passed command line), can string numeric used detect whether multiple data set data source run. case, example, fitting DAISIE model posterior distribution data. res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. par_upper_bound numeric defining upper limit integration parameter fitting relaxed-rate DAISIE model. DAISIE model applied relaxed-rate model, parameter can ignored left default influence model. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run DAISIE analysis — run_daisie_ml","text":"Nothing. Writes DAISIE analysis results .rds file. file stored file_path. directory file_path created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Run DAISIE analysis — run_daisie_ml","text":"Pedro Santos Neves, Joshua W. Lambert, Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Run DAISIE analysis — run_daisie_ml","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") run_daisie_ml( daisie_data = Galapagos_datalist, data_name = \"Galapagos_datalist\", model = \"cr_dd\", array_index = 1, cond = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":null,"dir":"Reference","previous_headings":"","what":"Runs a DAISIE simulation — run_sim","title":"Runs a DAISIE simulation — run_sim","text":"Runs DAISIE simulation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runs a DAISIE simulation — run_sim","text":"","code":"run_sim(daisie_data, model, lik_res, cond)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Runs a DAISIE simulation — run_sim","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free lik_res data frame results DAISIE maximum likelihood model. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS().","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Runs a DAISIE simulation — run_sim","text":"List output DAISIE simulation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":null,"dir":"Reference","previous_headings":"","what":"Read the results of run_daisie_ml() and compares model selection — sensitivity","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"Reads results run_daisie_ml() compares model selection determine sensitivity different data input model set models. run_daisie_ml() results expected located sub folders within results/ folder current working directory. sub folders must names elements data_names.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"","code":"sensitivity(data_names, full_output = FALSE, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"data_names vector strings names data sets want compare sensitivity. full_output boolean determining whether full model output returned. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"list 3 elements full_output FALSE, 4 elements TRUE. elements follows: best_fit_sensitivity character vector length one, reports whether best fit model sensitive input. model_selection_sensitivity character vector length one, reports whether rank (order) model selection sensitive input. model_selection_rank named list many elements models data_names. named list contains sorted named vector corresponding BIC value fit model. sort always ascending. full_output returned full_output TRUE. named list similar structure model_selection_rank. Instead named vectors BIC values, however, full run_daisie_ml() data frame output returned. one row data frame, parameter estimates, degrees freedom, convergence information BIC value.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"","code":"if (FALSE) { sensitivity( data_names = c(\"Azores\", \"Azores_alt_m\"), full_output = FALSE ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":null,"dir":"Reference","previous_headings":"","what":"Set up DAISIE_ML arguments — setup_2type_model","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"Set DAISIE_ML arguments","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"","code":"setup_2type_model(model, prop_type2_pool, low_rates = FALSE)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free prop_type2_pool numeric determining proportion mainland species pool composed type 2 species. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"named list DAISIE::DAISIE_ML() arguments.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"Luis M Valente, Pedro Santos Neves, Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"","code":"model <- \"cr_dd\" setup_model( model = model ) #> $ddmodel #> [1] 11 #> #> $idparsopt #> lac mu k gam laa #> 1 2 3 4 5 #> #> $parsfix #> NULL #> #> $idparsfix #> NULL #> #> $idparsnoshift #> [1] 6 7 8 9 10 #> #> $initparsopt #> lac mu k gam laa #> 0.95829023 0.81521667 186.44782309 0.09438888 1.17948246 #> #> $cs_version #> [1] 1 #>"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":null,"dir":"Reference","previous_headings":"","what":"Set up DAISIE_ML arguments — setup_model","title":"Set up DAISIE_ML arguments — setup_model","text":"Set DAISIE_ML arguments","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set up DAISIE_ML arguments — setup_model","text":"","code":"setup_model(model, low_rates = FALSE, par_upper_bound = Inf)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set up DAISIE_ML arguments — setup_model","text":"model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. par_upper_bound numeric defining upper limit integration parameter fitting relaxed-rate DAISIE model. DAISIE model applied relaxed-rate model, parameter can ignored left default influence model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set up DAISIE_ML arguments — setup_model","text":"named list DAISIE::DAISIE_ML() arguments.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Set up DAISIE_ML arguments — setup_model","text":"Luis M Valente, Pedro Santos Neves, Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set up DAISIE_ML arguments — setup_model","text":"","code":"model <- \"cr_dd\" setup_model( model = model ) #> $ddmodel #> [1] 11 #> #> $idparsopt #> lac mu k gam laa #> 1 2 3 4 5 #> #> $parsfix #> NULL #> #> $idparsfix #> NULL #> #> $idparsnoshift #> [1] 6 7 8 9 10 #> #> $initparsopt #> lac mu k gam laa #> 1.49976301 1.60932627 148.16579102 0.09281851 0.65453359 #> #> $cs_version #> [1] 1 #>"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":null,"dir":"Reference","previous_headings":"","what":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"Returns pars2 vector needed simple DAISIE_ML_CS() runs, facilitate computing loglikelihood cases. function assumed correct LL setup CS model, 1 type, constant rate equilibrium models. Tolerances technical parameters need specified, returned values match default values DAISIE::DAISIE_ML(). arguments without default values ddmodel cond, often varied checking model output. Regardless, default parameter values can forced meet specific needs complex models.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"","code":"setup_std_pars2( res = 100, ddmodel = 11, cond = 0, verbose = 0, island_ontogeny = NA, eqmodel = 0, tol = c(1e-04, 1e-05, 1e-07), maxiter = 1000 * round((1.25)^5), x_E = 0.95, x_I = 0.98 )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. ddmodel Sets model diversity-dependence: ddmodel = 0: diversity dependence ddmodel = 1: linear dependence speciation rate ddmodel = 11: linear dependence speciation rate immigration rate ddmodel = 2: exponential dependence speciation rate ddmodel = 21: exponential dependence speciation rate immigration rate cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). verbose simulation dataprep functions logical, Default = TRUE gives intermediate output printed. ML functions numeric determining intermediate output printed, Default = 0 print, verbose = 1 prints intermediate output parameters loglikelihood, verbose = 2 means also intermediate progress loglikelihood computation shown. island_ontogeny DAISIE_sim_time_dep(), DAISIE_ML_CS plotting string describing type island ontogeny. Can \"const\", \"beta\" beta function describing area time. functions numeric describing type island ontogeny. Can 0 constant, 1 beta function describing area time. ML functions island_ontogeny = NA assumes constant ontogeny. Time dependent estimation yet available development still ongoing. return error called case. eqmodel Sets equilibrium constraint can used likelihood optimization. available datatype = 'single'. eqmodel = 0 : equilibrium assumed eqmodel = 13 : near-equilibrium assumed endemics using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value eqmodel = 15 : near-equilibrium assumed endemics immigrants using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value, non-endemics must within x_I equilibrium value. tol Sets tolerances optimization. Consists : reltolx - relative tolerance parameter values optimization. reltolf - relative tolerance function value optimization. abstolx - absolute tolerance parameter values optimization. maxiter Sets maximum number iterations optimization. x_E Sets fraction equlibrium endemic diversity endemics assumed equilibrium; active eqmodel = 13 15. x_I Sets fraction equlibrium non-endemic diversity system assumed equilibrium; active eqmodel = 15.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"numeric vector length 12 containing pars2 DAISIE::DAISIE_ML()","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"","code":"std_pars2 <- setup_std_pars2()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"output list results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"","code":"summarize_bootstrap_results(daisie_data, mainland_n = 1000)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. mainland_n numeric stating number mainland species, number species can potentially colonize island. using clade-specific diversity dependence, value set 1 internally simulation. using island-wide diversity dependence, value set number mainland species.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"overall_results list results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"Rampal S. Etienne & Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"","code":"if (FALSE) { clado_rate <- 0.5 ext_rate <- 0.2 carr_cap <- Inf immig_rate <- 0.005 ana_rate <- 1 sim_pars <- c(clado_rate, ext_rate, carr_cap, immig_rate, ana_rate) set.seed(1) dataset_cs <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"CS\" ) dataset_iw <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"IW\" ) overall_results_cs <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_cs ) overall_results_iw <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_iw ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-161","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.6.1","title":"DAISIEutils 1.6.1","text":"Migrate now defunct Peregrine HPCC new Hábrók HPCC Prevent Inf passed relaxed rate model run_daisie_ml() (#33)","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-160","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.6.0","title":"DAISIEutils 1.6.0","text":"version R DAISIE incremented 4.2 4.4.0, respectively relaxed-rate DAISIE model now initial DAISIE optimisation get better initial conditions (run_daisie_ml()) Removed old documentation section causing warning","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-150","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.5.0","title":"DAISIEutils 1.5.0","text":"requires new argument run_daisie_ml() setup_model(): par_upper_bound, sets upper limit integration relaxed parameter. defaults Inf R function shell scripts, upper bound integration relaxed-rate DAISIE model. parameter ignored using standard constant-rate case (.e., relaxed-rate). Allow 2 type DAISIE ML analyses, handled run_daisie_2type_ml() adjacent function setup_2type_model(). Similarly add required R run_daisie_2type_ml.R script shell scripts submit_run_daisie_2type_ml.sh submit_run_daisie_2type_ml_long.sh run said analyses HPCC. Package depends CRAN DAISIE release instead GitHub repository. Now requires DAISIE >= v4.3.1 ensure latest ML related bugfixes used. Add new tests covering new cases. Add Rampal Etienne’s details zenodo release.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-140","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.4.0","title":"DAISIEutils 1.4.0","text":"Add new argument res change resolution DAISIE::DAISIE_ML_CS(). Default values allows backwards compatibility functions job scripts Peregrine.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-130","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.3.0","title":"DAISIEutils 1.3.0","text":"Can now extract single data set (replicate) data set stores several within list. Add support non-oceanic models (can chosen relevant functions start nonoceanic relevant functions).","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-121","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.2.1","title":"DAISIEutils 1.2.1","text":"Correct .zenodo.json automatic release archiving Zenodo.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-120","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.2.0","title":"DAISIEutils 1.2.0","text":"Reworked reference test file infrastructure use tempdir(). Added results_dir argument functions load /write file system allow user specify custom directory appropriate environment. default, NULL maintains previous behaviour, .e., saves loads folder results/ root working directory. Removed is_daisie_data() incomplete seldom used. May ported packages future. Rework create_output_folder() handle directory creation. file path generation now handled create_results_dir_path() assuming previous functionality new added flexibility via results_dir argument described . Add alternative (lower) CES rates run_daisie_ml() setup model allow certain datasets begin estimation valid parameters. Renamed argument data daisie_data consistency recent DAISIE related packages avoid conflicts base R’s data(). Add functions plot bootstrap results check model goodness fit: plot_bootstrap_results(), summarize_bootstrap_results() adding plot_sim_metrics() now split calc_sim_metrics(). Add setup_std_pars2() generate common pars2, useful development within ‘DAISIE’. run_daisie_ml() can now return ’s output session rather saving file setting results_dir NA. run_daisie_ml() uses lsodes default methode, line ‘DAISIE’. Style entire package ‘styler’. Require ‘DAISIE’ v4.2.1. longer depend private packages, ensure package can accessed users. Due new plot functions, depend ‘ggplot2’’cowplot’. Added upload_results.R upload_results.sh upload Google drive directly Peregrine. Added .zenodo.json metadata automatic Zenodo releases.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-110","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.1.0","title":"DAISIEutils 1.1.0","text":"choose_best_model() correctly handles results model estimated successfully, returns NA appropriately. sensitivity() now works correctly regardless number parameters used estimate chosen models. means relaxed-rate models model fitting returns results base DAISIE parameters accommodated. sensitivity() longer saves file instead returns results environment. Improved sensitivity() documentation. Depend install DAISIE v4.0.2.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-100","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.0.0","title":"DAISIEutils 1.0.0","text":"Complete overhaul package. Add run_daisie_ml() fit DAISIE models DAISIE datasets. Returns model fitting results BIC value. Add bootstrap_lr() conduct likelihood ratio bootstrap test two DAISIE models. Add bootstrap() conduct goodness fit bootstrapping test. Add sensitivity() calculate sensitivity model two alternative data sets.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-0009001","dir":"Changelog","previous_headings":"","what":"DAISIEutils 0.0.0.9001","title":"DAISIEutils 0.0.0.9001","text":"Create package skeleton. Add print_main_header(). Use default_params_doc.R document package. Write README.md stub. Add tests coverage. Added NEWS.md file track changes package.","code":""}] +[{"path":"https://tece-lab.github.io/DAISIEutils/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Pedro Santos Neves. Author, maintainer. Joshua W. Lambert. Author. Luis Valente. Author. Richèl J.C. Bilderbeek. Author. Rampal S. Etienne. Author.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Santos Neves P, Lambert J, Valente L, Bilderbeek R, Etienne R (2023). DAISIEutils: Utility Functions DAISIE Package. https://github.com/tece-lab/DAISIEutils, https://tece-lab.github.io/DAISIEutils/.","code":"@Manual{, title = {DAISIEutils: Utility Functions for the DAISIE Package}, author = {Pedro {Santos Neves} and Joshua W. Lambert and Luis Valente and Richèl J.C. Bilderbeek and Rampal S. Etienne}, year = {2023}, note = {https://github.com/tece-lab/DAISIEutils, https://tece-lab.github.io/DAISIEutils/}, }"},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"daisieutils","dir":"","previous_headings":"","what":"Utility Functions for the DAISIE Package","title":"Utility Functions for the DAISIE Package","text":"goal DAISIEutils collect useful utility functions used recurrently DAISIE projects. DAISIEutils companion package R package DAISIE. includes pipelines typical analyses using DAISIE’s maximum likelihood inference. Note: DAISIEutils depends latest CRAN release DAISIE. used older versions DAISIE package.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Utility Functions for the DAISIE Package","text":"can install released version DAISIEutils GitHub :","code":"install.packages(\"remotes\") remotes::install_github(\"tece-lab/DAISIEutils\")"},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"features","dir":"","previous_headings":"","what":"Features","title":"Utility Functions for the DAISIE Package","text":"DAISIEutils allows researcher easily accomplish following tasks: Choose specify number common DAISIE models, different combinations free initial parameters. Fit said models data, sampling number initial parameters minimize model convergence local optima. Choose best fitting models. Run bootstrap likelihood ratio tests. Test sensitivity results changing data sets.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/index.html","id":"supportquestions","dir":"","previous_headings":"","what":"Support/Questions","title":"Utility Functions for the DAISIE Package","text":"feature requests bug-reports, please submit issue. matters, contact authors: @Neves-P @joshwlambert.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":null,"dir":"Reference","previous_headings":"","what":"Birds of Azores archipelago — Azores","title":"Birds of Azores archipelago — Azores","text":"dataset containing age archipelago, number species mainland present island, colonising clade colonisation branching times, endemicity status, missing species, type species. Obtained parsed relaxedDAISIE project strictly illustration test purposes","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Birds of Azores archipelago — Azores","text":"","code":"Azores"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Birds of Azores archipelago — Azores","text":"object class list length 18: island_age Age island not_present Number mainland species colonise island colonist_name name colonising clade branching_times age island colonisation subsequent branching times clade stac Endemicity status clade missing_species Number species missing phylogeny clade type1or2 Defines type species clade, used 2-type analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Birds of Azores archipelago — Azores","text":"Valente et al. (2020) doi: https://doi.org/10.1038/s41586-020-2022-5 https://github.com/joshwlambert/relaxedDAISIE","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":null,"dir":"Reference","previous_headings":"","what":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"dataset containing age archipelago, number species mainland present island, colonising clade colonisation branching times, endemicity status, missing species, type species. Obtained parsed relaxedDAISIE project strictly illustration test purposes","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"","code":"Azores_alt_m"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"object class list length 18: island_age Age island not_present Number mainland species colonise island colonist_name name colonising clade branching_times age island colonisation subsequent branching times clade stac Endemicity status clade missing_species Number species missing phylogeny clade type1or2 Defines type species clade, used 2-type analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/Azores_alt_m.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Birds of Azores archipelago with alternative mainland species pool size — Azores_alt_m","text":"Valente et al. (2020) doi: https://doi.org/10.1038/s41586-020-2022-5 https://github.com/joshwlambert/relaxedDAISIE","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/DAISIEutils-package.html","id":null,"dir":"Reference","previous_headings":"","what":"DAISIEutils: Utility Functions for the DAISIE Package — DAISIEutils-package","title":"DAISIEutils: Utility Functions for the DAISIE Package — DAISIEutils-package","text":"goal DAISIEutils collect useful utility functions used recurently DAISIE projects. DAISIEutils companion package R package DAISIE.","code":""},{"path":[]},{"path":"https://tece-lab.github.io/DAISIEutils/reference/DAISIEutils-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"DAISIEutils: Utility Functions for the DAISIE Package — DAISIEutils-package","text":"Maintainer: Pedro Santos Neves p.m.santos.neves@rug.nl (ORCID) Authors: Joshua W. Lambert j.w.l.lambert@rug.nl (ORCID) Luis Valente luis.valente@naturalis.nl (ORCID) Richèl J.C. Bilderbeek richel@richelbilderbeek.nl (ORCID) Rampal S. Etienne r.s.etienne@rug.nl (ORCID)","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":null,"dir":"Reference","previous_headings":"","what":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"Runs bootstrapping DAISIE model determine parameter precision","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"","code":"bootstrap( daisie_data, data_name, model, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"Nothing. Writes bootstrapping results .rds file. file stored $HOME/results/data_name running cluster /results/data_name running locally. directory created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runs a bootstrapping on a DAISIE model to determine parameter precision — bootstrap","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") bootstrap( daisie_data = Galapagos_datalist, data_name = \"Galapagos_datalist\", model = \"cr_dd\", array_index = 1, cond = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":null,"dir":"Reference","previous_headings":"","what":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"Runs parameteric bootstrapping likelihood ratio test two DAISIE models","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"","code":"bootstrap_lr( daisie_data, data_name, model_1, model_2, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model_1 string model run. list options see documentation model parameter run_daisie_ml(). model_2 string model run. list options see documentation model parameter run_daisie_ml(). array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"Nothing. Writes bootstrapping results .rds file. file stored file_path. directory file_path created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/bootstrap_lr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runs a parameteric bootstrapping likelihood ratio test on two DAISIE models — bootstrap_lr","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") bootstrap_lr( daisie_data = Galapagos_datalist, model_1 = \"cr_dd\", model_2 = \"cr_di\", array_index = 1, cond = 1, ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute Bayesian Information Criterion of a model — calc_bic","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"Compute Bayesian Information Criterion model","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"","code":"calc_bic(results, daisie_data)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"results data frame containing model results created run_daisie_ml(). results DAISIE::DAISIE_ML_CS() bic, saved RDS file run_daisie_ml(). daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"Numeric value BIC","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_bic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Compute Bayesian Information Criterion of a model — calc_bic","text":"Joshua W. Lambert, Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"Calculates loglikelihood ratio two models","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"","code":"calc_loglik_ratio(model_1_lik_res, model_2_lik_res)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"model_1_lik_res data frame results DAISIE maximum likelihood model. model_2_lik_res data frame results DAISIE maximum likelihood model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_loglik_ratio.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the loglikelihood ratio between two models — calc_loglik_ratio","text":"Numeric likelihood ratio","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"Calculates p-value rejecting model distribution likelihood ratios","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"","code":"calc_p_value(daisie_data, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_p_value.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates p-value for rejecting a model from a distribution of likelihood\nratios — calc_p_value","text":"Numeric p-value","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates power to detect the true model — calc_power","title":"Calculates power to detect the true model — calc_power","text":"Calculates power detect true model","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates power to detect the true model — calc_power","text":"","code":"calc_power(daisie_data, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates power to detect the true model — calc_power","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_power.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates power to detect the true model — calc_power","text":"Numeric power","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates summary metrics from a simulation — calc_sim_metrics","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"Calculates summary metrics simulation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"","code":"calc_sim_metrics(daisie_data)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"List simulation metrics","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/calc_sim_metrics.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculates summary metrics from a simulation — calc_sim_metrics","text":"Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks if jobs were run with the same seed — check_rep_seeds","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"Checks every log file inside folder record used seed. Returns duplicated seeds corresponding job arrays.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"","code":"check_rep_seeds(logs_path)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"logs_path Character path folder containing logs. log files present, plain text format.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"data frame four columns. line contains information one result duplicated seed. lines duplicated seeds logs. Columns follows: Data: character vector name data set duplicates found. Models: numeric corresponding array index. empty duplicates found. Seeds: numeric corresponding seed duplicated. Array_indices: numeric corresponding array index.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"function preferred method checking presence repeated seeds. However, fail log files generated older versions package, expects seed array information always location. encounter issues, try running check_rep_seeds_depr() instead. cases, give preference function better optimization log output parsing possible.","code":""},{"path":[]},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks if jobs were run with the same seed — check_rep_seeds","text":"","code":"if (FALSE) { repeated_seeds <- check_rep_seeds(logs_path = \"/logs/\") }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"Checks every log file inside folder record used seed returns duplicated seeds corresponding job arrays.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"","code":"check_rep_seeds_depr(logs_path)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"logs_path Character path folder containing logs. log files present, plain text format.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"data frame four columns. line contains information one result duplicated seed. lines duplicated seeds logs. Columns follows: Data: character vector name data set duplicates found. Models: numeric corresponding array index. empty duplicates found. Seeds: numeric corresponding seed duplicated. Array_indices: numeric corresponding array index.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"function, lines containing scraped values can anywhere file, occurred older versions package. Checking thus less efficient preference given check_rep_seeds() cases, unless older log files checked. check_rep_seeds() fail older log files.","code":""},{"path":[]},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/check_rep_seeds_depr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Checks if jobs were run with the same seed on older logs — check_rep_seeds_depr","text":"","code":"if (FALSE) { repeated_seeds <- check_rep_seeds_depr(logs_path = \"/logs/\") }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":null,"dir":"Reference","previous_headings":"","what":"From multiple seeds, choose the best model fit — choose_best_model","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"multiple seeds, choose best model fit","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"","code":"choose_best_model(model_lik_res)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"model_lik_res data frame results DAISIE maximum likelihood model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"list length one, data frame 1 row containing best estimated models given seeds, determined loglik. model estimated successfully, returns similar structure fields NA.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/choose_best_model.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"From multiple seeds, choose the best model fit — choose_best_model","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":null,"dir":"Reference","previous_headings":"","what":"Create output folder — create_output_folder","title":"Create output folder — create_output_folder","text":"Create output folder","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create output folder — create_output_folder","text":"","code":"create_output_folder(data_name, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create output folder — create_output_folder","text":"data_name String. used name created output folder. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create output folder — create_output_folder","text":"Creates appropriate directory. Returns string path output object. default, Hábrók, folder $HOME/results/$data_name. called another environment, folder getwd()/results/$data_name. Alternatively, another valid root can specified, resulting results_dir/$data_name.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create output folder — create_output_folder","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_output_folder.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create output folder — create_output_folder","text":"","code":"if (FALSE) { create_output_folder( data_name = \"results_folder\" ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":null,"dir":"Reference","previous_headings":"","what":"Create results directory path — create_results_dir_path","title":"Create results directory path — create_results_dir_path","text":"Create results directory path","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create results directory path — create_results_dir_path","text":"","code":"create_results_dir_path(data_name, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create results directory path — create_results_dir_path","text":"data_name String. used name created output folder. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create results directory path — create_results_dir_path","text":"String platform appropriate file path used results directory given data set.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Create results directory path — create_results_dir_path","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/create_results_dir_path.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create results directory path — create_results_dir_path","text":"","code":"results_dir_path <- create_results_dir_path(data_name = \"Azores\")"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":null,"dir":"Reference","previous_headings":"","what":"Default parameters documentation — default_params_doc","title":"Default parameters documentation — default_params_doc","text":"Default parameters documentation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default parameters documentation — default_params_doc","text":"","code":"default_params_doc( model, data_name, results_root_folder, daisie_data, array_index, file_path, results, cond, optimmethod, methode, model_1, model_2, model_1_lik_res, model_2_lik_res, model_lik_res, lik_res, data_names, full_output, seed, test, logs_path, results_dir, overall_results, sumstats, ylim4, title, ddmodel, verbose, island_ontogeny, eqmodel, tol, maxiter, x_E, x_I, mainland_n, low_rates, rep_index, res, prop_type2_pool, par_upper_bound )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default parameters documentation — default_params_doc","text":"model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free data_name String. used name created output folder. results_root_folder Character. path root folder containing subfolders. subfolder contains result files analysis runs. daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. array_index single numeric array index. used naming output file. file_path system directory output files stored. results data frame containing model results created run_daisie_ml(). results DAISIE::DAISIE_ML_CS() bic, saved RDS file run_daisie_ml(). cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). model_1 string model run. list options see documentation model parameter run_daisie_ml(). model_2 string model run. list options see documentation model parameter run_daisie_ml(). model_1_lik_res data frame results DAISIE maximum likelihood model. model_2_lik_res data frame results DAISIE maximum likelihood model. model_lik_res data frame results DAISIE maximum likelihood model. lik_res data frame results DAISIE maximum likelihood model. data_names vector strings names data sets want compare sensitivity. full_output boolean determining whether full model output returned. seed Integer value used seed Mersenne-Twister. value determined Sys.time() array_index ensure parallel jobs different seeds. last 6 digits Sys.time() (integer) used. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed. logs_path Character path folder containing logs. log files present, plain text format. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. overall_results summary results obtained summarize_bootstrap_results(). sumstats vector number species, number colonization, size largest clade rank largest clade empirical data ylim4 maximum plot rank largest clade. title title plot. ddmodel Sets model diversity-dependence: ddmodel = 0: diversity dependence ddmodel = 1: linear dependence speciation rate ddmodel = 11: linear dependence speciation rate immigration rate ddmodel = 2: exponential dependence speciation rate ddmodel = 21: exponential dependence speciation rate immigration rate verbose simulation dataprep functions logical, Default = TRUE gives intermediate output printed. ML functions numeric determining intermediate output printed, Default = 0 print, verbose = 1 prints intermediate output parameters loglikelihood, verbose = 2 means also intermediate progress loglikelihood computation shown. island_ontogeny DAISIE_sim_time_dep(), DAISIE_ML_CS plotting string describing type island ontogeny. Can \"const\", \"beta\" beta function describing area time. functions numeric describing type island ontogeny. Can 0 constant, 1 beta function describing area time. ML functions island_ontogeny = NA assumes constant ontogeny. Time dependent estimation yet available development still ongoing. return error called case. eqmodel Sets equilibrium constraint can used likelihood optimization. available datatype = 'single'. eqmodel = 0 : equilibrium assumed eqmodel = 13 : near-equilibrium assumed endemics using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value eqmodel = 15 : near-equilibrium assumed endemics immigrants using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value, non-endemics must within x_I equilibrium value. tol Sets tolerances optimization. Consists : reltolx - relative tolerance parameter values optimization. reltolf - relative tolerance function value optimization. abstolx - absolute tolerance parameter values optimization. maxiter Sets maximum number iterations optimization. x_E Sets fraction equlibrium endemic diversity endemics assumed equilibrium; active eqmodel = 13 15. x_I Sets fraction equlibrium non-endemic diversity system assumed equilibrium; active eqmodel = 15. mainland_n numeric stating number mainland species, number species can potentially colonize island. using clade-specific diversity dependence, value set 1 internally simulation. using island-wide diversity dependence, value set number mainland species. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. rep_index string default \"NULL\" (string true NULL due passed command line), can string numeric used detect whether multiple data set data source run. case, example, fitting DAISIE model posterior distribution data. res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. prop_type2_pool numeric determining proportion mainland species pool composed type 2 species. par_upper_bound numeric defining upper limit integration parameter fitting relaxed-rate DAISIE model. DAISIE model applied relaxed-rate model, parameter can ignored left default influence model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/default_params_doc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default parameters documentation — default_params_doc","text":"Nothing","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":null,"dir":"Reference","previous_headings":"","what":"List all available models — get_available_models","title":"List all available models — get_available_models","text":"List available models","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List all available models — get_available_models","text":"","code":"get_available_models()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List all available models — get_available_models","text":"character vector named codes available models.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"List all available models — get_available_models","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/get_available_models.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List all available models — get_available_models","text":"","code":"available_models <- DAISIEutils:::get_available_models()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if code is running on Hábrók HPCC — is_on_cluster","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"Check code running Hábrók HPCC","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"","code":"is_on_cluster()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"Boolean. TRUE called Hábrók HPCC, FALSE .","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/is_on_cluster.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check if code is running on Hábrók HPCC — is_on_cluster","text":"","code":"on_cluster <- is_on_cluster()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"output list results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"","code":"plot_bootstrap_results( overall_results, sumstats = c(65, 5, 28, 1), ylim4 = 0.7, title = NULL )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"overall_results summary results obtained summarize_bootstrap_results(). sumstats vector number species, number colonization, size largest clade rank largest clade empirical data ylim4 maximum plot rank largest clade. title title plot.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"Rampal S. Etienne & Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_bootstrap_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes summary results of bootstrap simulations useful for plotting — plot_bootstrap_results","text":"","code":"if (FALSE) { clado_rate <- 0.5 ext_rate <- 0.2 carr_cap <- Inf immig_rate <- 0.005 ana_rate <- 1 sim_pars <- c(clado_rate, ext_rate, carr_cap, immig_rate, ana_rate) set.seed(1) dataset_cs <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"CS\" ) dataset_iw <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"IW\" ) overall_results_cs <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_cs ) overall_results_iw <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_iw ) par(mfrow = c(2, 4), cex.lab = 1.5, cex.main = 1.5) DAISIEutils::plot_bootstrap_results( overall_results = overall_results_cs, title = \"Simulated under CS\" ) DAISIEutils::plot_bootstrap_results( overall_results = overall_results_iw, title = \"Simulated under IW\" ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots metrics from simulations — plot_sim_metrics","title":"Plots metrics from simulations — plot_sim_metrics","text":"Plots metrics simulations","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots metrics from simulations — plot_sim_metrics","text":"","code":"plot_sim_metrics(sim_metrics)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots metrics from simulations — plot_sim_metrics","text":"sim_metrics list metrics output calc_sim_metrics()","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots metrics from simulations — plot_sim_metrics","text":"none Four plots shown: histogram number species, histogram number colonizations, histogram largest clade size histogram rank largest clade","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/plot_sim_metrics.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plots metrics from simulations — plot_sim_metrics","text":"Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":null,"dir":"Reference","previous_headings":"","what":"Print session and run info to console/log file — print_metadata","title":"Print session and run info to console/log file — print_metadata","text":"Useful call start normal job scripts run cluster metadata recorded log files.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print session and run info to console/log file — print_metadata","text":"","code":"print_metadata(data_name, model, array_index, seed, methode, optimmethod)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print session and run info to console/log file — print_metadata","text":"data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. seed Integer value used seed Mersenne-Twister. value determined Sys.time() array_index ensure parallel jobs different seeds. last 6 digits Sys.time() (integer) used. methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print session and run info to console/log file — print_metadata","text":"Nothing. Prints session run info used DAISIE console.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Print session and run info to console/log file — print_metadata","text":"Message used print function arguments. retain formatting, simple sessioninfo::session_info() used session info, uses print. Hence, session_info() go stdout, remaining output function go stderr.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Print session and run info to console/log file — print_metadata","text":"Pedro Santos Neves, Luis Valente, Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/print_metadata.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Print session and run info to console/log file — print_metadata","text":"","code":"if (FALSE) { print_metadata( data_name = \"Galapagos_datalist\", model = \"cr_di\", array_index = 1, seed = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Reads run_daisie_ml() results — read_model_results","title":"Reads run_daisie_ml() results — read_model_results","text":"Reads run_daisie_ml() results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Reads run_daisie_ml() results — read_model_results","text":"","code":"read_model_results(results_root_folder)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Reads run_daisie_ml() results — read_model_results","text":"results_root_folder Character. path root folder containing subfolders. subfolder contains result files analysis runs.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Reads run_daisie_ml() results — read_model_results","text":"Nested list. First layer corresponds data sets, per folders found results_root_folder. second layer corresponds models run dataset, containing 1 row long data frame alternate seed runs model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/read_model_results.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Reads run_daisie_ml() results — read_model_results","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":null,"dir":"Reference","previous_headings":"","what":"Run 2 type DAISIE analysis — run_daisie_2type_ml","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"Run 2 type DAISIE analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"","code":"run_daisie_2type_ml( daisie_data, data_name, model, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, low_rates = FALSE, rep_index = \"NULL\", res = 100, prop_type2_pool, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. rep_index string default \"NULL\" (string true NULL due passed command line), can string numeric used detect whether multiple data set data source run. case, example, fitting DAISIE model posterior distribution data. res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. prop_type2_pool numeric determining proportion mainland species pool composed type 2 species. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"Nothing. Writes DAISIE analysis results .rds file. file stored file_path. directory file_path created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"Pedro Santos Neves, Joshua W. Lambert, Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_2type_ml.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Run 2 type DAISIE analysis — run_daisie_2type_ml","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") run_daisie_2type_ml( daisie_data = Galapagos_datalist, data_name = \"Galapagos_datalist\", model = \"cr_dd\", array_index = 1, cond = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":null,"dir":"Reference","previous_headings":"","what":"Run DAISIE analysis — run_daisie_ml","title":"Run DAISIE analysis — run_daisie_ml","text":"Run DAISIE analysis","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Run DAISIE analysis — run_daisie_ml","text":"","code":"run_daisie_ml( daisie_data, data_name, model, array_index, cond, methode = \"lsodes\", optimmethod = \"subplex\", results_dir = NULL, low_rates = FALSE, rep_index = \"NULL\", res = 100, par_upper_bound = Inf, test = FALSE )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Run DAISIE analysis — run_daisie_ml","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. data_name String. used name created output folder. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free array_index single numeric array index. used naming output file. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). methode Method ODE-solver. Supported Boost ODEINT solvers (steppers) : \"odeint::runge_kutta_cash_karp54\" \"odeint::runge_kutta_fehlberg78\" \"odeint::runge_kutta_dopri5\" \"odeint::bulirsch_stoer\" without odeint::-prefix, \\link{deSolve}{ode}() method assumed. default method overall \"lsodes\" \\link{DAISIE_ML_CS}() \"ode45\" \\link[deSolve]{ode}() \\link{DAISIE_ML_IW}(). optimmethod Method used likelihood optimization. Default subplex (see \\link[subplex]{subplex}() full details). Alternative \"simplex\" method previous versions. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. rep_index string default \"NULL\" (string true NULL due passed command line), can string numeric used detect whether multiple data set data source run. case, example, fitting DAISIE model posterior distribution data. res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. par_upper_bound numeric defining upper limit integration parameter fitting relaxed-rate DAISIE model. DAISIE model applied relaxed-rate model, parameter can ignored left default influence model. test boolean, defaults FALSE. Set TRUE testing purposes, fix seed.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Run DAISIE analysis — run_daisie_ml","text":"Nothing. Writes DAISIE analysis results .rds file. file stored file_path. directory file_path created exist.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Run DAISIE analysis — run_daisie_ml","text":"Pedro Santos Neves, Joshua W. Lambert, Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_daisie_ml.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Run DAISIE analysis — run_daisie_ml","text":"","code":"if (FALSE) { data(Galapagos_datalist, package = \"DAISIE\") run_daisie_ml( daisie_data = Galapagos_datalist, data_name = \"Galapagos_datalist\", model = \"cr_dd\", array_index = 1, cond = 1 ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":null,"dir":"Reference","previous_headings":"","what":"Runs a DAISIE simulation — run_sim","title":"Runs a DAISIE simulation — run_sim","text":"Runs DAISIE simulation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runs a DAISIE simulation — run_sim","text":"","code":"run_sim(daisie_data, model, lik_res, cond)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Runs a DAISIE simulation — run_sim","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free lik_res data frame results DAISIE maximum likelihood model. cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS().","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/run_sim.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Runs a DAISIE simulation — run_sim","text":"List output DAISIE simulation","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":null,"dir":"Reference","previous_headings":"","what":"Read the results of run_daisie_ml() and compares model selection — sensitivity","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"Reads results run_daisie_ml() compares model selection determine sensitivity different data input model set models. run_daisie_ml() results expected located sub folders within results/ folder current working directory. sub folders must names elements data_names.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"","code":"sensitivity(data_names, full_output = FALSE, results_dir = NULL)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"data_names vector strings names data sets want compare sensitivity. full_output boolean determining whether full model output returned. results_dir string path directory results stored can found. example, data question () stored folder_with_res/$data_name, results_dir \"folder_with_res\". Defaults NULL, indicates default directories used. Default directories : * $HOME/results/$data_name cluster * getwd()/results/$data_name called another environment .na(results_dir), object returned R session saved file.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"list 3 elements full_output FALSE, 4 elements TRUE. elements follows: best_fit_sensitivity character vector length one, reports whether best fit model sensitive input. model_selection_sensitivity character vector length one, reports whether rank (order) model selection sensitive input. model_selection_rank named list many elements models data_names. named list contains sorted named vector corresponding BIC value fit model. sort always ascending. full_output returned full_output TRUE. named list similar structure model_selection_rank. Instead named vectors BIC values, however, full run_daisie_ml() data frame output returned. one row data frame, parameter estimates, degrees freedom, convergence information BIC value.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/sensitivity.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read the results of run_daisie_ml() and compares model selection — sensitivity","text":"","code":"if (FALSE) { sensitivity( data_names = c(\"Azores\", \"Azores_alt_m\"), full_output = FALSE ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":null,"dir":"Reference","previous_headings":"","what":"Set up DAISIE_ML arguments — setup_2type_model","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"Set DAISIE_ML arguments","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"","code":"setup_2type_model(model, prop_type2_pool, low_rates = FALSE)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free prop_type2_pool numeric determining proportion mainland species pool composed type 2 species. low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"named list DAISIE::DAISIE_ML() arguments.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"Luis M Valente, Pedro Santos Neves, Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_2type_model.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set up DAISIE_ML arguments — setup_2type_model","text":"","code":"model <- \"cr_dd\" setup_model( model = model ) #> $ddmodel #> [1] 11 #> #> $idparsopt #> lac mu k gam laa #> 1 2 3 4 5 #> #> $parsfix #> NULL #> #> $idparsfix #> NULL #> #> $idparsnoshift #> [1] 6 7 8 9 10 #> #> $initparsopt #> lac mu k gam laa #> 1.440610e+00 1.377048e+00 1.680143e+02 1.734061e-03 1.513600e+00 #> #> $cs_version #> [1] 1 #>"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":null,"dir":"Reference","previous_headings":"","what":"Set up DAISIE_ML arguments — setup_model","title":"Set up DAISIE_ML arguments — setup_model","text":"Set DAISIE_ML arguments","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set up DAISIE_ML arguments — setup_model","text":"","code":"setup_model(model, low_rates = FALSE, par_upper_bound = Inf)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set up DAISIE_ML arguments — setup_model","text":"model string model run. Models follows: \"cr_dd\" Clade specific model - diversity dependent. parameters free. \"cr_di\" Clade specific model - diversity independent (K = Inf). parameters free. \"cr_dd_0laa\" Clade specific model - diversity dependent anagenesis (laa fixed zero). parameters free. \"cr_di_0laa\" Clade specific model - diversity independent (K = Inf) anagenesis (laa fixed zero). parameters free. \"cr_di_0lac\" Clade specific model - diversity indendent (K = Inf) cladogenesis (lac fixed zero). parameters free. \"cr_dd_0lac\" Clade specific model - diversity dependent cladogenesis (lac fixed zero). parameters free. \"rr_lac_di\" Clade specific model - diversity independent (K = Inf) relaxed cladogenesis. parameters free. \"rr_lac_dd\" Clade specific model - diversity dependent relaxed cladogenesis. parameters free. \"rr_mu_di\" Clade specific model - diversity independent (K = Inf) relaxed extinction. parameters free. \"rr_mu_dd\" Clade specific model - diversity dependent relaxed extinction. parameters free. \"rr_k\" Clade specific model - diversity dependent relaxed carrying capacity. parameters free. \"rr_gam_di\" Clade specific model - diversity independent (K = Inf) relaxed colonisation. parameters free. \"rr_gam_dd\" Clade specific model - diversity dependent relaxed colonisation. parameters free. \"rr_laa_di\" Clade specific model - diversity independent (K = Inf) relaxed anagenesis. parameters free. \"rr_laa_dd\" Clade specific model - diversity dependent relaxed anagenesis. parameters free. \"rr_mu_di_0lac\" Clade specific model - diversity independent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_mu_dd_0lac\" Clade specific model - diversity dependent, relaxed extinction, cladogenesis (lac fixed zero). parameters free. \"rr_k_0lac\" Clade specific model - diversity dependent, relaxed carrying capacity, cladogenesis (lac fixed zero). parameters free. \"rr_gam_di_0lac\" Clade specific model - diversity independent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"r_gam_dd_0lac\" Clade specific model - diversity dependent, relaxed colonisation, cladogenesis (lac fixed zero). parameters free. \"rr_laa_di_0lac\" Clade specific model - diversity independent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"r_laa_dd_0lac\" Clade specific model - diversity dependent, relaxed anagenesis, cladogenesis (lac fixed zero). parameters free. \"rr_lac_di_0laa\" Clade specific model - diversity independent, relaxed cladogenesis, anagenesis (laa fixed zero) \"rr_lac_dd_0laa\" Clade specific model - diversity dependent \"rr_mu_di_0laa\" Clade specific model - diversity independent \"rr_mu_dd_0laa\" Clade specific model - diversity dependent \"rr_k_0laa\" Clade specific model - diversity dependent \"rr_gam_di_0laa\" Clade specific model - diversity independent, relaxed colonisation, anagenesis (laa fixed zero). parameters free \"rr_gam_dd_0laa\" Clade specific model - diversity dependent, relaxed colonisation, anagenesis (laa fixed zero). parameters free low_rates Boolean determining whether random sampling initial parameter estimates sampled broad range (FALSE) restricted range initial rates ensured smaller (TRUE). latter helps using large datasets may fail initial likelihood computation higher rates sampled broad range rates. par_upper_bound numeric defining upper limit integration parameter fitting relaxed-rate DAISIE model. DAISIE model applied relaxed-rate model, parameter can ignored left default influence model.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set up DAISIE_ML arguments — setup_model","text":"named list DAISIE::DAISIE_ML() arguments.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Set up DAISIE_ML arguments — setup_model","text":"Luis M Valente, Pedro Santos Neves, Joshua W. Lambert","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_model.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set up DAISIE_ML arguments — setup_model","text":"","code":"model <- \"cr_dd\" setup_model( model = model ) #> $ddmodel #> [1] 11 #> #> $idparsopt #> lac mu k gam laa #> 1 2 3 4 5 #> #> $parsfix #> NULL #> #> $idparsfix #> NULL #> #> $idparsnoshift #> [1] 6 7 8 9 10 #> #> $initparsopt #> lac mu k gam laa #> 0.63644094 0.48772227 186.99077689 0.08761113 3.41426549 #> #> $cs_version #> [1] 1 #>"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":null,"dir":"Reference","previous_headings":"","what":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"Returns pars2 vector needed simple DAISIE_ML_CS() runs, facilitate computing loglikelihood cases. function assumed correct LL setup CS model, 1 type, constant rate equilibrium models. Tolerances technical parameters need specified, returned values match default values DAISIE::DAISIE_ML(). arguments without default values ddmodel cond, often varied checking model output. Regardless, default parameter values can forced meet specific needs complex models.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"","code":"setup_std_pars2( res = 100, ddmodel = 11, cond = 0, verbose = 0, island_ontogeny = NA, eqmodel = 0, tol = c(1e-04, 1e-05, 1e-07), maxiter = 1000 * round((1.25)^5), x_E = 0.95, x_I = 0.98 )"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"res numeric determining resolution likelihood calculations, sets limit maximum number species probability must computed, must larger size largest clade. ddmodel Sets model diversity-dependence: ddmodel = 0: diversity dependence ddmodel = 1: linear dependence speciation rate ddmodel = 11: linear dependence speciation rate immigration rate ddmodel = 2: exponential dependence speciation rate ddmodel = 21: exponential dependence speciation rate immigration rate cond integer specifying conditioning, described DAISIE::DAISIE_ML_CS(). verbose simulation dataprep functions logical, Default = TRUE gives intermediate output printed. ML functions numeric determining intermediate output printed, Default = 0 print, verbose = 1 prints intermediate output parameters loglikelihood, verbose = 2 means also intermediate progress loglikelihood computation shown. island_ontogeny DAISIE_sim_time_dep(), DAISIE_ML_CS plotting string describing type island ontogeny. Can \"const\", \"beta\" beta function describing area time. functions numeric describing type island ontogeny. Can 0 constant, 1 beta function describing area time. ML functions island_ontogeny = NA assumes constant ontogeny. Time dependent estimation yet available development still ongoing. return error called case. eqmodel Sets equilibrium constraint can used likelihood optimization. available datatype = 'single'. eqmodel = 0 : equilibrium assumed eqmodel = 13 : near-equilibrium assumed endemics using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value eqmodel = 15 : near-equilibrium assumed endemics immigrants using deterministic equation endemics immigrants. Endemics must within x_E equilibrium value, non-endemics must within x_I equilibrium value. tol Sets tolerances optimization. Consists : reltolx - relative tolerance parameter values optimization. reltolf - relative tolerance function value optimization. abstolx - absolute tolerance parameter values optimization. maxiter Sets maximum number iterations optimization. x_E Sets fraction equlibrium endemic diversity endemics assumed equilibrium; active eqmodel = 13 15. x_I Sets fraction equlibrium non-endemic diversity system assumed equilibrium; active eqmodel = 15.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"numeric vector length 12 containing pars2 DAISIE::DAISIE_ML()","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"Pedro Santos Neves","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/setup_std_pars2.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fills pars2 vector for most common DAISIE ML CS runs — setup_std_pars2","text":"","code":"std_pars2 <- setup_std_pars2()"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"output list results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"","code":"summarize_bootstrap_results(daisie_data, mainland_n = 1000)"},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"daisie_data list, conforming DAISIE object format. Usually preprocessed DAISIE::DAISIE_dataprep(), see documentation details. Otherwise may generated via simulations, using DAISIE::DAISIE_sim_cr() friends. mainland_n numeric stating number mainland species, number species can potentially colonize island. using clade-specific diversity dependence, value set 1 internally simulation. using island-wide diversity dependence, value set number mainland species.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"overall_results list results","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"Rampal S. Etienne & Luis Valente","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/reference/summarize_bootstrap_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes summary results of bootstrap simulations useful for plotting — summarize_bootstrap_results","text":"","code":"if (FALSE) { clado_rate <- 0.5 ext_rate <- 0.2 carr_cap <- Inf immig_rate <- 0.005 ana_rate <- 1 sim_pars <- c(clado_rate, ext_rate, carr_cap, immig_rate, ana_rate) set.seed(1) dataset_cs <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"CS\" ) dataset_iw <- DAISIE::DAISIE_sim_cr( time = 10, M = 1000, pars = sim_pars, replicates = 10, plot_sims = FALSE, verbose = FALSE, divdepmodel = \"IW\" ) overall_results_cs <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_cs ) overall_results_iw <- DAISIEutils::summarize_bootstrap_results( daisie_data = dataset_iw ) }"},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-162","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.6.2","title":"DAISIEutils 1.6.2","text":"Prevent parameter values upper bound passed relaxed rate model run_daisie_ml() (#34). Lower value given initial parameter value estimated infinite relaxed rate model run_daisie_ml().","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-161","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.6.1","title":"DAISIEutils 1.6.1","text":"Migrate now defunct Peregrine HPCC new Hábrók HPCC Prevent Inf passed relaxed rate model run_daisie_ml() (#33)","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-160","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.6.0","title":"DAISIEutils 1.6.0","text":"version R DAISIE incremented 4.2 4.4.0, respectively relaxed-rate DAISIE model now initial DAISIE optimisation get better initial conditions (run_daisie_ml()) Removed old documentation section causing warning","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-150","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.5.0","title":"DAISIEutils 1.5.0","text":"requires new argument run_daisie_ml() setup_model(): par_upper_bound, sets upper limit integration relaxed parameter. defaults Inf R function shell scripts, upper bound integration relaxed-rate DAISIE model. parameter ignored using standard constant-rate case (.e., relaxed-rate). Allow 2 type DAISIE ML analyses, handled run_daisie_2type_ml() adjacent function setup_2type_model(). Similarly add required R run_daisie_2type_ml.R script shell scripts submit_run_daisie_2type_ml.sh submit_run_daisie_2type_ml_long.sh run said analyses HPCC. Package depends CRAN DAISIE release instead GitHub repository. Now requires DAISIE >= v4.3.1 ensure latest ML related bugfixes used. Add new tests covering new cases. Add Rampal Etienne’s details zenodo release.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-140","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.4.0","title":"DAISIEutils 1.4.0","text":"Add new argument res change resolution DAISIE::DAISIE_ML_CS(). Default values allows backwards compatibility functions job scripts Peregrine.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-130","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.3.0","title":"DAISIEutils 1.3.0","text":"Can now extract single data set (replicate) data set stores several within list. Add support non-oceanic models (can chosen relevant functions start nonoceanic relevant functions).","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-121","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.2.1","title":"DAISIEutils 1.2.1","text":"Correct .zenodo.json automatic release archiving Zenodo.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-120","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.2.0","title":"DAISIEutils 1.2.0","text":"Reworked reference test file infrastructure use tempdir(). Added results_dir argument functions load /write file system allow user specify custom directory appropriate environment. default, NULL maintains previous behaviour, .e., saves loads folder results/ root working directory. Removed is_daisie_data() incomplete seldom used. May ported packages future. Rework create_output_folder() handle directory creation. file path generation now handled create_results_dir_path() assuming previous functionality new added flexibility via results_dir argument described . Add alternative (lower) CES rates run_daisie_ml() setup model allow certain datasets begin estimation valid parameters. Renamed argument data daisie_data consistency recent DAISIE related packages avoid conflicts base R’s data(). Add functions plot bootstrap results check model goodness fit: plot_bootstrap_results(), summarize_bootstrap_results() adding plot_sim_metrics() now split calc_sim_metrics(). Add setup_std_pars2() generate common pars2, useful development within ‘DAISIE’. run_daisie_ml() can now return ’s output session rather saving file setting results_dir NA. run_daisie_ml() uses lsodes default methode, line ‘DAISIE’. Style entire package ‘styler’. Require ‘DAISIE’ v4.2.1. longer depend private packages, ensure package can accessed users. Due new plot functions, depend ‘ggplot2’’cowplot’. Added upload_results.R upload_results.sh upload Google drive directly Peregrine. Added .zenodo.json metadata automatic Zenodo releases.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-110","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.1.0","title":"DAISIEutils 1.1.0","text":"choose_best_model() correctly handles results model estimated successfully, returns NA appropriately. sensitivity() now works correctly regardless number parameters used estimate chosen models. means relaxed-rate models model fitting returns results base DAISIE parameters accommodated. sensitivity() longer saves file instead returns results environment. Improved sensitivity() documentation. Depend install DAISIE v4.0.2.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-100","dir":"Changelog","previous_headings":"","what":"DAISIEutils 1.0.0","title":"DAISIEutils 1.0.0","text":"Complete overhaul package. Add run_daisie_ml() fit DAISIE models DAISIE datasets. Returns model fitting results BIC value. Add bootstrap_lr() conduct likelihood ratio bootstrap test two DAISIE models. Add bootstrap() conduct goodness fit bootstrapping test. Add sensitivity() calculate sensitivity model two alternative data sets.","code":""},{"path":"https://tece-lab.github.io/DAISIEutils/news/index.html","id":"daisieutils-0009001","dir":"Changelog","previous_headings":"","what":"DAISIEutils 0.0.0.9001","title":"DAISIEutils 0.0.0.9001","text":"Create package skeleton. Add print_main_header(). Use default_params_doc.R document package. Write README.md stub. Add tests coverage. Added NEWS.md file track changes package.","code":""}]
NEWS.md
run_daisie_ml()