version 2.1.7

cran · Oct 8, 2021 · 5486599 · 5486599
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,9 +1,9 @@
 Package: IMIFA
 Type: Package
-Date: 2021-05-24
+Date: 2021-10-07
 Title: Infinite Mixtures of Infinite Factor Analysers and Related
         Models
-Version: 2.1.6
+Version: 2.1.7
 Authors@R: c(person("Keefe", "Murphy", email = "keefe.murphy@mu.ie", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7709-3159")),
              person("Cinzia", "Viroli", email = "cinzia.viroli@unibo.it", role = "ctb", comment = c(ORCID = "0000-0002-3278-5266")),
              person("Isobel Claire", "Gormley", email = "claire.gormley@ucd.ie", role = "ctb", comment = c(ORCID = "0000-0001-7713-681X")))
@@ -17,17 +17,17 @@ LazyData: true
 Imports: matrixStats (>= 0.53.1), mclust (>= 5.4), mvnfast, Rfast (>=
         1.9.8), slam, viridisLite
 Suggests: gmp (>= 0.5-4), knitr, mcclust, rmarkdown, Rmpfr
-RoxygenNote: 7.1.1
+RoxygenNote: 7.1.2
 VignetteBuilder: knitr
 Collate: 'MainFunction.R' 'Diagnostics.R' 'FullConditionals.R'
         'Gibbs_FA.R' 'Gibbs_IFA.R' 'Gibbs_IMFA.R' 'Gibbs_IMIFA.R'
         'Gibbs_MFA.R' 'Gibbs_MIFA.R' 'Gibbs_OMFA.R' 'Gibbs_OMIFA.R'
         'IMIFA.R' 'PlottingFunctions.R' 'SimulateData.R' 'data.R'
 NeedsCompilation: no
-Packaged: 2021-05-24 16:27:36 UTC; Keefe
+Packaged: 2021-10-07 17:32:30 UTC; Keefe
 Author: Keefe Murphy [aut, cre] (<https://orcid.org/0000-0002-7709-3159>),
   Cinzia Viroli [ctb] (<https://orcid.org/0000-0002-3278-5266>),
   Isobel Claire Gormley [ctb] (<https://orcid.org/0000-0001-7713-681X>)
 Maintainer: Keefe Murphy <keefe.murphy@mu.ie>
 Repository: CRAN
-Date/Publication: 2021-05-24 16:50:05 UTC
+Date/Publication: 2021-10-08 08:20:05 UTC
diff --git a/MD5 b/MD5
@@ -1,57 +1,58 @@
-175a52f5685bd1a4e6d61e2e6b0df9bf *DESCRIPTION
-7984ab11221544306180a9cf9cc69cdc *NAMESPACE
-fd033604f82d5e5a76411f6327e1a5ec *R/Diagnostics.R
-535912213a5bb4b54108fac14ea05822 *R/FullConditionals.R
-c9758e6bd78a6b4b5b04e62febc695d2 *R/Gibbs_FA.R
-490d89b0b8370a9355165f5ee9fc4845 *R/Gibbs_IFA.R
-a15ec15281402392818c8f6cef25f1fa *R/Gibbs_IMFA.R
-c84cd82ba9e91895d706e7612425e793 *R/Gibbs_IMIFA.R
-90dfc671e7bd008b197dbe77776058db *R/Gibbs_MFA.R
-0f50c6609d639962cc7eac464a30ac33 *R/Gibbs_MIFA.R
-acb1bae1593331bd008e6bbc1f4d406a *R/Gibbs_OMFA.R
-1cc95dcb089b1eacab7cb4c1ce77977e *R/Gibbs_OMIFA.R
-1e2e4a842a99cf8575385ca5198d1945 *R/IMIFA.R
-8f7db5405333c779739b13f0ae6c0794 *R/MainFunction.R
-677f5cef1a658bb60fadbe84c1af7672 *R/PlottingFunctions.R
-7f328389820bec778e76dd0603c15684 *R/SimulateData.R
+cb7e244d9f5c0e8449d333df7c5e50d2 *DESCRIPTION
+43636f2890fe5ca7805f4e9cee26e683 *NAMESPACE
+175b346495c3f86771d4e1c6fe3ec91a *R/Diagnostics.R
+d35cd5390257507da5948f7cdfa657c1 *R/FullConditionals.R
+ca7e3e89725a62a66047bd344ab892d5 *R/Gibbs_FA.R
+58d61e6e8665272cd29c8d954a795557 *R/Gibbs_IFA.R
+95a591f1642794f1d0e53b99eabf31d7 *R/Gibbs_IMFA.R
+60a2278b86fcce000f0104715cf3016a *R/Gibbs_IMIFA.R
+34ca478d2f11c97f25ebc67a7a0a8a03 *R/Gibbs_MFA.R
+9f9940e66f78bcf7e733a687ce7ce204 *R/Gibbs_MIFA.R
+80a5d499d0feba66da97b7b27adcac26 *R/Gibbs_OMFA.R
+24cb65d011f517568eb93953944afff4 *R/Gibbs_OMIFA.R
+5428c3b41fb0fc1af15b7e65c7a21756 *R/IMIFA.R
+66c4ca2aecc64c519de5ccf681e7e964 *R/MainFunction.R
+bec75bb39b9c13d2c8ebfefb2443925a *R/PlottingFunctions.R
+fdf39f8459a292aac124a0872267260d *R/SimulateData.R
 c18d7934dea4c410e2e4414027ddf896 *R/data.R
-34ef4cd91594ba06f529ed22ca7a16b7 *README.md
-8c4fb9a940faa4bb485df9ed8e3859f5 *build/partial.rdb
-007e14e7b7ed5c87e2e76035fd4b1fb3 *build/vignette.rds
+a6cc30de4b7dba84696b198324700e2f *README.md
+e3dff798a5283233aea289cdebab9fa5 *build/partial.rdb
+b5707e6864a7c3558e0ce6067cbe79bf *build/vignette.rds
 8a1546836eba4e124ab4a8258d56c3e9 *data/USPSdigits.rda
 0561ac6b39266e6e9b645b7b2ee31c64 *data/coffee.rda
 c0bcb7c2dd21f9748941a039b377be74 *data/olive.rda
-8042066b01805c990a476e5c559f0c6a *inst/CITATION
-740ed748bc363a314916a4f04820236c *inst/NEWS.md
-9f5d49c968942cdb9aff3510283e9dff *inst/doc/IMIFA.R
-bc04a50703d34e3c1ef5d8fb1fc260de *inst/doc/IMIFA.Rmd
-9017a867e8a91cd9fc7825328a96ddce *inst/doc/IMIFA.html
+612860916c824ec5d9b27b800dae990f *inst/CITATION
+1cf6af9086fe0fcd40aa7a9462d7f05f *inst/NEWS.md
+0a7abd5dac266d9b70d57d46855ff71c *inst/doc/IMIFA.R
+866c5f1041e6db49aaf7896a099a8234 *inst/doc/IMIFA.Rmd
+1480033714f872d148f33ea0e362aca2 *inst/doc/IMIFA.html
 31925b942368610fc313af56989d9adf *man/G_moments.Rd
 88422a650bc07f1d06b1b6c5d170875d *man/G_priorDensity.Rd
-7742790e84f7b8702f936cd5bd4b0907 *man/IMIFA-package.Rd
+33959197ee3cb8a5a896ca42ed208ef4 *man/IMIFA-package.Rd
 56cdda484c2370de672298800c81d3d8 *man/IMIFA_news.Rd
 a8d99db1eeb0254fb5b0594ed33d3a04 *man/Ledermann.Rd
-44c596807368d568d74730ffccf99efc *man/MGP_check.Rd
+c7ed7724b83e701ae1e79f812c28f2f1 *man/MGP_check.Rd
 c7e4978690d2642ef4a6f018379911ae *man/PGMM_dfree.Rd
 024cc3af21cd2866f430946d44c50574 *man/Procrustes.Rd
 72446a862e5a5eac13ca5bd7f2047975 *man/USPSdigits.Rd
-81b463f77780a6d19688b1605d45d34f *man/Zsimilarity.Rd
+9ade94eb3b3ee095a90e7c57ee0f90bd *man/Zsimilarity.Rd
 d09fbf41fe01186f58086f2c9babec4c *man/bnpControl.Rd
 8ad430d031386654deae38e0f3222fab *man/coffee.Rd
 76d55ab2b3be581b0db49459c640e26b *man/get_IMIFA_results.Rd
 5b271eb6d92f7e968eeeb908a99699d4 *man/gumbel_max.Rd
 f43fc1d238bd1b4b89d884fc918d8819 *man/heat_legend.Rd
 f4ad348f54042a3406a1dab3c6ac5676 *man/is.cols.Rd
 1a0a122c8bf344670fc791ed30457334 *man/is.posi_def.Rd
+42202b99f21d0089d3a85b951d664227 *man/ltrgamma.Rd
 e7d36a4ca1d9f67fa9a66120ca4cb58e *man/mat2cols.Rd
-155df1622ff6dbab2d202a9fdcd85b8b *man/mcmc_IMIFA.Rd
-83a4d8085d465ab22d98700ed0f3013e *man/mgpControl.Rd
+cf34cf5497aec25849cae0f36f4148ea *man/mcmc_IMIFA.Rd
+34655ea2de87f82f700b9608557afd13 *man/mgpControl.Rd
 f0cba41295ed186614847d637cf2a9ed *man/mixfaControl.Rd
 376d35460fbfb90198d8f42b84cdd454 *man/olive.Rd
 6374921bc6bf3b5d2e45b9b8739e2300 *man/pareto_scale.Rd
 6230b4d8bf19a308769fd4edfa41d38e *man/plot.Results_IMIFA.Rd
 8e13feda5e28254d4efe8d4687eec58a *man/plot_cols.Rd
-bb46f39e23c8c03c85677c2332058b4e *man/post_conf_mat.Rd
+ce857a605b54938c11719bb8a70f6b82 *man/post_conf_mat.Rd
 66168bf2be3ab5240ee81b482df50c3a *man/psi_hyper.Rd
 e5ab57edc415abf586409f2369b1bf95 *man/rDirichlet.Rd
 c0226719b4b87c95c8401f6f6db86c56 *man/scores_MAP.Rd
@@ -60,5 +61,5 @@ a49403d852d540f0139ad2783db53357 *man/shift_GA.Rd
 0ad7c9d4066d6deba11f08b32d9a68cf *man/show_digit.Rd
 b305d00003cc68b16f53e3b9b580898f *man/sim_IMIFA.Rd
 f7c823779a6472870cc8cd89184ee27c *man/storeControl.Rd
-bc04a50703d34e3c1ef5d8fb1fc260de *vignettes/IMIFA.Rmd
+866c5f1041e6db49aaf7896a099a8234 *vignettes/IMIFA.Rmd
 39268a288f379004b29ce4e77ee340b1 *vignettes/res_olive_IMIFA__Edited-Vignette-only-Version.rda
diff --git a/NAMESPACE b/NAMESPACE
@@ -22,6 +22,7 @@ export(PGMM_dfree)
 export(Procrustes)
 export(Zsimilarity)
 export(bnpControl)
+export(exp_ltrgamma)
 export(get_IMIFA_results)
 export(gumbel_max)
 export(heat_legend)
@@ -36,6 +37,7 @@ export(plot_cols)
 export(post_conf_mat)
 export(psi_hyper)
 export(rDirichlet)
+export(rltrgamma)
 export(scores_MAP)
 export(shift_GA)
 export(show_IMIFA_digit)

diff --git a/R/Diagnostics.R b/R/Diagnostics.R
@@ -577,7 +577,7 @@ get_IMIFA_results.IMIFA        <- function(sims = NULL, burnin = 0L, thinning =
     }
 
     if(learn.d)     {
-      discount   <- as.vector(sims[[G.ind]][[Q.ind]]$discount[store])
+      discount   <- drop(sims[[G.ind]][[Q.ind]]$discount[store])
       post.disc  <- mean(discount)
       post.kappa <- sum(discount == 0)/n.store
       var.disc   <- Var(discount)
@@ -632,19 +632,19 @@ get_IMIFA_results.IMIFA        <- function(sims = NULL, burnin = 0L, thinning =
       Q.tab      <- table(Q.store, dnn=NULL)
       Q.prob     <- prop.table(Q.tab)
     }
-    Q.mode       <- if(G1) unlist(lapply(Q.tab, function(qt) as.numeric(names(qt[qt == max(qt)])[1L]))) else as.numeric(names(Q.tab[Q.tab == max(Q.tab)])[1L])
-    Q.med        <- if(G1) stats::setNames(ceiling(matrixStats::rowMedians(Q.store) * 2)/2, gnames)     else ceiling(Median(Q.store) * 2)/2
+    Q.mode       <- if(G1) unlist(lapply(Q.tab, function(qt) as.numeric(names(qt[qt == max(qt)])[1L])))  else as.numeric(names(Q.tab[Q.tab == max(Q.tab)])[1L])
+    Q.med        <- if(G1) stats::setNames(ceiling(matrixStats::rowMedians(Q.store) * 2)/2, gnames)      else ceiling(Median(Q.store) * 2)/2
     if(!Q.T)  {
       Q          <- switch(EXPR=Q.meth, mode=Q.mode, floor(Q.med))
     } else    {
-      Q          <- if(G.T) Q else stats::setNames(if(length(Q) == G) Q else rep(Q, G), gnames)
+      Q          <- if(G.T) Q else stats::setNames(if(length(Q) == G) Q    else rep(Q, G), gnames)
     }
     Q.CI         <- if(G1) round(rowQuantiles(Q.store, probs=conf.levels)) else round(stats::quantile(Q.store, conf.levels))
     GQ.temp4     <- list(Q = Q, Q.Mode = Q.mode, Q.Median = Q.med,
                          Q.CI = Q.CI, Q.Probs = Q.prob, Q.Counts = Q.tab,
-                         Stored.Q = if(clust.ind) Q.store else as.vector(Q.store),
+                         Stored.Q = if(clust.ind) Q.store else drop(Q.store),
                          Q.Last = Q.store[,TN.store])
-    GQ.res       <- if(inf.G)   c(GQ.temp1, GQ.temp4) else c(list(G = G), GQ.temp4)
+    GQ.res       <- if(inf.G)   c(GQ.temp1, GQ.temp4)     else c(list(G = G), GQ.temp4)
     GQ.res       <- if(cshrink) c(GQ.res, list(post.sigma = stats::setNames(rowMeans2(sigmas), gnames))) else GQ.res
    #GQ.res       <- if(gshrink) c(GQ.res, list(post.SIGMA = mean(SIGMAS))) else GQ.res
     GQ.res       <- c(GQ.res, list(Criteria = GQ.temp2))
@@ -1114,6 +1114,7 @@ get_IMIFA_results.IMIFA        <- function(sims = NULL, burnin = 0L, thinning =
   attr(result, "Store")        <- tmp.store
   attr(result, "Switch")       <- sw
  #attr(result, "Thresh")       <- attr(sims, "Thresh")
+  attr(result, "Truncated")    <- attr(sims, "Truncate")
   attr(result, "TuneZeta")     <- attr(sims, "TuneZeta")
   attr(result, "Uni.Meth")     <- uni.meth
   attr(result, "Varnames")     <- varnames