version 1.1.0

DESCRIPTION

@@ -1,14 +1,14 @@
 Package: makemyprior
 Type: Package
 Title: Intuitive Construction of Joint Priors for Variance Parameters
-Version: 1.0.1
+Version: 1.1.0
 Authors@R: c(
     person("Ingeborg Gullikstad", "Hem", email = "ingeborg.hem@ntnu.no", role = c("cre", "aut")),
     person("Geir-Arne", "Fuglstad", role = "aut"),
     person("Andrea", "Riebler", role = "aut") )
 Description: Tool for easy prior construction and visualization. It helps to formulates joint prior distributions for variance parameters in latent Gaussian models. The resulting prior is robust and can be created in an intuitive way. A graphical user interface (GUI) can be used to choose the joint prior, where the user can click through the model and select priors. An extensive guide is available in the GUI. The package allows for direct inference with the specified model and prior. Using a hierarchical variance decomposition, we formulate a joint variance prior that takes the whole model structure into account. In this way, existing knowledge can intuitively be incorporated at the level it applies to. Alternatively, one can use independent variance priors for each model components in the latent Gaussian model.
 License: GPL (>= 2)
-Date: 2022-02-22
+Date: 2022-03-14
 Encoding: UTF-8
 LazyData: true
 Imports: ggplot2, Matrix, methods, shiny, shinyjs, shinyBS, visNetwork,
@@ -19,10 +19,10 @@ Additional_repositories: https://inla.r-inla-download.org/R/stable/
 VignetteBuilder: knitr
 RoxygenNote: 7.1.2
 NeedsCompilation: no
-Packaged: 2022-02-21 12:40:07 UTC; ingebogh
+Packaged: 2022-03-14 10:49:22 UTC; ingebogh
 Author: Ingeborg Gullikstad Hem [cre, aut],
   Geir-Arne Fuglstad [aut],
   Andrea Riebler [aut]
 Maintainer: Ingeborg Gullikstad Hem <ingeborg.hem@ntnu.no>
 Repository: CRAN
-Date/Publication: 2022-02-21 13:30:08 UTC
+Date/Publication: 2022-03-14 14:20:02 UTC

MD5

@@ -1,14 +1,14 @@
-2ac25e0ca90eb8b8458753f25aabb02f *DESCRIPTION
-aad1621c0b4648cb98b54bcd0ef431b0 *NAMESPACE
-a4239368e5e3d53699bc6a3807d0020f *NEWS.md
+7fa250e587f004032bfdf1d8fb78bf17 *DESCRIPTION
+696a21842a923c23e18a07f2fe6ce795 *NAMESPACE
+5f951df0bad8f4028be14562190075b1 *NEWS.md
 0712b679191f1f4e5c32d8c8728a6b28 *R/custom_stan_code_functions.R
-9142c515f1bb441529a67de535b02b32 *R/data.R
+7b41818a1a132d8a69639c643628a69d *R/data.R
 fb8118a8fbf828e60a26e28ccca8a2c1 *R/functions_both.R
 c6c5557a8c1996c63ad66526240b8062 *R/functions_calculate_pc_prior.R
-7acaa4333077f509b62ddaca5d49a484 *R/functions_for_server_shiny.R
-1c0662c270f61602cb814461105871bc *R/functions_posterior_diagnostics.R
+78729579db2cc69e5c0fe5d97ee34156 *R/functions_for_server_shiny.R
+3cd45f7b2861f8f2888520827f78acdb *R/functions_posterior_diagnostics.R
 f7d9875ee3d89a7c0f16f487a5086b42 *R/guide_modules.R
-8a9cb6145cced850d2212e6831ca0053 *R/make_prior_object_functions.R
+78bedd5bc2df27607ed3fc7fa6dcde8b *R/make_prior_object_functions.R
 f2b8c2c545433f84f2fa9a8a3b3513f9 *R/modules.R
 9847489e6d1e5f326f945119b56245c9 *R/pc_prior_functions.R
 bbff300e1d4396a8857b2af894fef6ef *R/server.R
@@ -21,39 +21,41 @@ e1ce9c170db213728b7256841ca6d6af *data/neonatal_data.rda
 25aaad97322a37661bbce15286b00d7a *data/wheat_data.rda
 6284a9c32500b63743b14c505e9e2db4 *inst/doc/latin_square.R
 b867067c4fc5505049dff8530c8c21c1 *inst/doc/latin_square.Rmd
-3249777f8cebd5a8c09796dd1093b5ba *inst/doc/latin_square.html
+5ab291d02d2383a1956b51aa7681fb67 *inst/doc/latin_square.html
 f06caa598702def411205906b2ceb39c *inst/doc/make_prior.R
 ce74fea6ce238678471e9ef569962f11 *inst/doc/make_prior.Rmd
-8ad1839786b1b17a0ade9c636933cca2 *inst/doc/make_prior.html
+75df23f8d274c8854063657e3dbaad8e *inst/doc/make_prior.html
 c4367592886b0e77a62197fd405a2fd7 *inst/doc/neonatal_mortality.R
 e1bfd6dcc318f96d57d022739238ac56 *inst/doc/neonatal_mortality.Rmd
-800068dfd188a018cdc315e3e3dc164a *inst/doc/neonatal_mortality.html
+de415a8b30a401a4ebbb2c9fbe6be2e8 *inst/doc/neonatal_mortality.html
 f096eb129319edf8d347a286cc6ddcf3 *inst/doc/wheat_breeding.R
 3c695254f66b60fcfc91731e5a060f4d *inst/doc/wheat_breeding.Rmd
-983b386c2d6cea0565a46c66214bd383 *inst/doc/wheat_breeding.html
+c4052bf1b5a287631dd4244547fe974a *inst/doc/wheat_breeding.html
 15b48dd6eef6e477ec33324eeba49d18 *inst/full_file.stan
 43689165b956214527b58651142b9707 *inst/include/jacobian_function_general.stan
 39ce1cd35ee972a86488627b46ebbc20 *inst/include/latent_models.stan
 92f6d237206afe44b53ce46ab0584b7c *inst/include/variance_priors.stan
 6559fc7d25fa643ad3eec5d7663117d3 *inst/neonatal.graph
-b2b6e1cf3c994cdd57df2e6afd4ecf26 *man/compile_stan.Rd
+11f6715e14584bedb8297ff86627194e *man/compile_stan.Rd
 e1e44beb3cd9f9f6dbfbae1138cfc596 *man/create_stan_file.Rd
-0c9b6473b40b70d75829f366dd4abb34 *man/eval_pc_prior.Rd
+5486a1f6d968f91182bcb18fc2668837 *man/eval_joint_prior.Rd
+32f0fcd9af8189cde980e9e9028f4555 *man/eval_pc_prior.Rd
 e0c06015c694415a00d3bce50b993ee9 *man/expit.Rd
-a05ded7b03a9bebe2ec335f475d5bf96 *man/extract_posterior_effect.Rd
-d3598a6877c616e4624f6ee877816589 *man/extract_posterior_parameter.Rd
+43a7a2ebe106321fa77d08bf5b8b183d *man/extract_posterior_effect.Rd
+a652ba6b5038d22d46a307769bb26f25 *man/extract_posterior_parameter.Rd
 d8e078e2222744cafc4be055665b0476 *man/find_pc_prior_param.Rd
-0f7cf9b832f1cf74785eac6ed7b6efc6 *man/inference_inla.Rd
-c9058250e84ccf4fa4913c4397dcb92a *man/inference_stan.Rd
-281c5aa12e7fa84c64c44741274b94ae *man/latin_data.Rd
+63034b6d3f2fa3513bea9e27e43719a4 *man/get_parameter_order.Rd
+3573ee583b3fee2c6f2e92ddf58d3480 *man/inference_inla.Rd
+c4d2a3e45991640168b8b78f6268b59d *man/inference_stan.Rd
+986eb9623be700556d10cd161b71e00c *man/latin_data.Rd
 b4c88eae4440963943a21bd7f76d49dd *man/logit.Rd
 03c50fda00c0363b9229e80c44fcea93 *man/make_prior.Rd
-14bd8a13b861588b0d1bbffbca09594d *man/makemyprior_example_model.Rd
+e5bbebd81bde6fee4dd227920c8fc4ce *man/makemyprior_example_model.Rd
 32b8cabec1a09144fb04d0bf9131744d *man/makemyprior_gui.Rd
 f7fb30a87db85104a0584d0b38948d22 *man/makemyprior_models.Rd
-dd0ed517a8854befa67d070d260065de *man/makemyprior_plotting.Rd
+c4191f0ab0fdadc77ba7af4d405fd54d *man/makemyprior_plotting.Rd
 1a4f2dbf437ed90b0f6cb8ba5bdf0da5 *man/mc.Rd
-71423a7d3051781d831b4daf5871abc5 *man/neonatal_data.Rd
+b6d557168440659b6bfd96272761e7cd *man/neonatal_data.Rd
 2ce142c20a10fc7ef7380aa44050a317 *man/plot.mmp_prior.Rd
 46da07d51c22a5237b6f103005725e2e *man/plot_marginal_prior.Rd
 56f4200ecc1e359962fce09dda515cc5 *man/plot_posterior_fixed.Rd
@@ -66,7 +68,7 @@ da25e6682285bea8781d17fbe23d3227 *man/plot_tree_structure.Rd
 bbb4a599022a0026bd2f2d4c664fb60d *man/scale_precmat.Rd
 3ab508e91e89aa31d188dcfef749c95d *man/summary.mmp_prior.Rd
 ff20f38edea6ac39cb451ed0ff637e77 *man/typical_variance.Rd
-890d27705adf84db235fffda8309db9c *man/wheat_data.Rd
+71908178abef2f32003012b3a34e8801 *man/wheat_data.Rd
 b867067c4fc5505049dff8530c8c21c1 *vignettes/latin_square.Rmd
 ce74fea6ce238678471e9ef569962f11 *vignettes/make_prior.Rmd
 e1bfd6dcc318f96d57d022739238ac56 *vignettes/neonatal_mortality.Rmd

NAMESPACE

@@ -11,14 +11,17 @@ S3method(summary,mmp_prior)
 S3method(summary,mmp_stan)
 export(compile_stan)
 export(create_stan_file)
+export(eval_joint_prior)
 export(eval_pc_prior)
 export(expit)
 export(extract_posterior_effect)
 export(extract_posterior_parameter)
 export(find_pc_prior_param)
+export(get_parameter_order)
 export(inference_inla)
 export(inference_stan)
 export(logit)
+export(make_eval_prior_data)
 export(make_prior)
 export(makemyprior_example_model)
 export(makemyprior_gui)

NEWS.md

@@ -1,5 +1,10 @@
 
 
+# makemyprior 1.1.0
+
+Added functionality to generalize the package, through simple usage of the joint HD prior.
+
+
 # makemyprior 1.0.1
 
 Minor bug fixes.

R/data.R

@@ -14,7 +14,6 @@
 #' \dontrun{
 #'
 #' vignette("wheat_breeding", package = "makemyprior")
-#'
 #' }
 #'
 #' if (interactive() && requireNamespace("rstan")){
@@ -47,6 +46,7 @@
 #' }
 #'
 #' \dontrun{
+#'
 #' posterior <- inference_stan(prior, iter = 150, warmup = 50,
 #'                             chains = 1, seed = 1)
 #'
@@ -76,7 +76,6 @@
 #' \dontrun{
 #'
 #' vignette("latin_square", package = "makemyprior")
-#'
 #' }
 #'
 #' if (interactive() && requireNamespace("rstan")){
@@ -103,6 +102,7 @@
 #' }
 #'
 #' \dontrun{
+#'
 #' posterior <- inference_stan(prior, iter = 15000, warmup = 5000,
 #'                             seed = 1, init = "0", chains = 1)
 #'
@@ -132,7 +132,6 @@
 #' \dontrun{
 #'
 #' vignette("neonatal_mortaily", package = "makemyprior")
-#'
 #' }
 #'
 #' if (interactive() && requireNamespace("rstan")){
@@ -164,6 +163,7 @@
 #' }
 #'
 #' \dontrun{
+#'
 #' posterior <- inference_stan(prior, iter = 15000, warmup = 5000,
 #'                             seed = 1, init = "0", chains = 1)
 #'

R/functions_for_server_shiny.R

@@ -1377,7 +1377,7 @@ get_prior_expr <- function(prior_data, node_data, param = c("cw", "totvar", "wei
   if (param == "cw"){
 
     if (prior_data$prior == "pc0") {
-      param_name <- sprintf("\\sigma_{%s}", gsub("_", "\\_", prior_data$name, fixed = TRUE), "}")
+      param_name <- sprintf("\\sigma_{%s}", gsub("_", "\\_", prior_data$name, fixed = TRUE)) #, "}")
       prior_expr <- sprintf("\\mathrm{PC}_{\\mathrm{0}}(%s, %s)", prior_data$param[1], prior_data$param[2])
     } else if (prior_data$prior == "jeffreys"){
       param_name <- sprintf("\\sigma_{%s}^2", gsub("_", "\\_", prior_data$name, fixed = TRUE))
@@ -1386,7 +1386,7 @@ get_prior_expr <- function(prior_data, node_data, param = c("cw", "totvar", "wei
       param_name <- sprintf("\\sigma_{%s}^2", gsub("_", "\\_", prior_data$name, fixed = TRUE))
       prior_expr <- paste0("\\mathrm{InvGam}(", prior_data$param[1], ",", prior_data$param[2], ")")
     } else if (prior_data$prior == "hc"){
-      param_name <- sprintf("\\sigma_{%s}", gsub("_", "\\_", prior_data$name, fixed = TRUE), "}")
+      param_name <- sprintf("\\sigma_{%s}", gsub("_", "\\_", prior_data$name, fixed = TRUE)) #, "}")
       prior_expr <- paste0("\\mathrm{HC}(", prior_data$param[1], ")")
     }
 

R/functions_posterior_diagnostics.R

@@ -796,9 +796,9 @@ plot_posterior_precision <- function(obj){
 
 #' Extract the posterior of a random effect
 #'
-#' #' Extract the posterior of a random effect in the model for inference done with Stan
+#' Extract the posterior of a random effect in the model for inference done with Stan
 #' @param obj An object from \code{inference_stan}.
-#' @param effname Name of the effect, same name as in the data.
+#' @param effname Name of the random effect, same name as in the data.
 #' @keywords posterior
 #' @return Returns a matrix with the posterior samples of the chosen effect
 #' @examples
@@ -837,7 +837,7 @@ extract_posterior_effect <- function(obj, effname){
 #'
 #' @param obj An object from \code{inference_stan}.
 #' @param param Name of the variance parameter, which is the same as the name of the corresponding
-#' fixed or random effect in the data. Intercept is denoted 'intercept'.
+#' fixed or random effect in the data. Intercept is denoted 'intercept', and residual variance is denoted 'eps'.
 #' @keywords posterior
 #' @return Returns a vector with the posterior samples of the chosen parameter, on variance scale for
 #' variances parameters and original (the common) scale for fixed effect coefficients
@@ -1192,7 +1192,7 @@ plot_marginal_prior <- function(x, obj, param, sd = FALSE){
 #' @param param Which weight to plot, indicated using syntax shown when printing (do not need to include the
 #' \code{w[..]} part to indicate that it is a variance proportion, but can be included). Print the prior object
 #' to see syntax for each weight.
-#' @param logitscale Return prior on logitscale? (default \code{FALSE}).
+#' @param logitscale Is the input \code{x} on logit-scale? (default \code{FALSE}).
 #' @return Returns density for the given variance proportion.
 #' @examples
 #' ex_prior <- makemyprior_example_model()