version 0.8-5

Author: suyusung

CHANGELOG

@@ -1,3 +1,20 @@
+2024-05-4  Yu-Sung Su     <[email protected]>
+    * DESCRIPTION (Version, Date): 0.8-5
+    * incorporate patches suggested by CRAN
+    * R/jags: add new parameter checkMissing = FALSE
+    * R/mcmc2bugs: add new parameter checkMissing = FALSE
+    * R/as.bugs.array2: add a patch to cases where levels of categorical variables have missing.
+        1. add new parameter checkMissing = FALSE, When set to TRUE, this option will verify the 
+            presence of missing data within the parameters, typically focusing on categorical 
+            variables or levels within Multilevel Models (MLM). If missing data is detected, 
+            the function will attempt to return a sim.list object containing NA values to 
+            indicate the missingness. It is generally advised against enabling this option. 
+            Instead, it is recommended to ensure that all variables provided to the jags() 
+            function are free from missing data before proceeding with the analysis.
+        2. it will now spell out warning message when categorical variables with missing data, users
+            should be careful about the output results.
+    * NAMESPACE: fix issues between Author and Authro@R
+
 2021-08-05 Yu-Sung Su     <[email protected]>
       * fix various issues suggested by Will Landau
 

DESCRIPTION

@@ -1,21 +1,24 @@
 Package: R2jags
-Version: 0.7-1.1
-Date: 2021-08-05
+Version: 0.8-5
+Date: 2024-05-01
 Title: Using R to Run 'JAGS'
-Author: Yu-Sung Su <[email protected]>,
-        Masanao Yajima <[email protected]>,
+Authors@R: c(person("Yu-Sung", "Su", role =  c("aut", "cre"), 
+		email = "[email protected]", 
+		comment = c(ORCID = "0000-0001-5021-8209")),
+	     person("Masanao", "Yajima", email = "[email protected]", role = "aut")
+		)
+Author: Yu-Sung Su [aut, cre] (<https://orcid.org/0000-0001-5021-8209>),
+  Masanao Yajima [aut]
 Maintainer: Yu-Sung Su <[email protected]>
 BugReports: https://github.com/suyusung/R2jags/issues/
 Depends: R (>= 2.14.0), rjags (>= 3-3)
+Suggests: testthat (>= 3.0.0)
 Imports: abind, coda (>= 0.13), graphics, grDevices, methods,
-        R2WinBUGS, parallel, stats, utils
+        R2WinBUGS, parallel, stats, stringr, utils
 SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
 Description: Providing wrapper functions to implement Bayesian analysis in JAGS.  Some major features include monitoring convergence of a MCMC model using Rubin and Gelman Rhat statistics, automatically running a MCMC model till it converges, and implementing parallel processing of a MCMC model for multiple chains.
 License: GPL (> 2)
-RoxygenNote: 7.1.1
-Suggests: testthat (>= 3.0.0)
-Config/testthat/edition: 3
 NeedsCompilation: no
-Packaged: 2024-02-04 20:09:16 UTC; ripley
+Packaged: 2024-05-04 11:43:21 UTC; yusung
 Repository: CRAN
-Date/Publication: 2024-02-05 08:15:27 UTC
+Date/Publication: 2024-05-04 12:50:02 UTC

MD5

@@ -1,27 +1,28 @@
-225db27ff5043d97292791af501fc127 *CHANGELOG
-703d08b1d4460a53e3463b70c14f6bfe *DESCRIPTION
-7756418df5cb9f5eddb9cedde0f2fb11 *NAMESPACE
+d1e90403a82fc2133b09badb579175ad *CHANGELOG
+7712c12873b0c06d264b4cf8c7613d05 *DESCRIPTION
+3a5facc9680703fabf76cc9317eb3367 *NAMESPACE
 0993ec3c619611d40927f6a4b24f9f91 *R/AllClass.R
-65e8671c8fbf9de2f49416201f041bfa *R/as.bugs.array2.R
-3d051481132ba73a38f117e0a544842c *R/as.mcmc.R
+de6ba4efcaa658ade6f69483f63fdc50 *R/as.bugs.array2.R
+277a4853017c68d07ba6817bd20381cc *R/as.mcmc.R
 9e6b25427b6c52ebdc74e9c431abc55c *R/attach.jags.R
 46e343f5bcfbc633064ada1a8933f78a *R/autojags.R
-67ee6f9913a0372002b9db3d9d3b35ee *R/jags.R
-dd0789cc2d85e9fe05c75190888f6cac *R/jags.sims.R
+ff6d52ce77e326d305a5d291a73f277a *R/jags.R
+7cb48206684061510a25d7976411ed22 *R/jags.sims.R
 a11f0bc0296d1e57fe6b827e97f24a86 *R/jags2.R
 4b1abee38647e8af6636c71f13cd5510 *R/jags2bugs.R
 290c44ab85aca43cfc2d56504af84f86 *R/jagsParallel.R
-f84f5317262e71e94270bf600d217b63 *R/mcmc2bugs.R
+60bfe7aa49a5fb0689c84c8f00e2640a *R/mcmc2bugs.R
 5f45c187679ee5855226de41e1618b12 *R/plot.R
 c1ff7891fcb484cf531c2dc205a67fb2 *R/print.R
 256ff74ae7f2d740d75ed706a615ba30 *R/recompile.R
 3843b38a6c53f3c4eec045cbf087dd20 *R/traceplot.R
 d8a7cc60b636be2563414d771da07dfd *R/update.R
 c228c7d0dc1a92b3a0f3a16e16669e52 *R/util.R
+a3c507e13de0fc31d125d233b347ce2d *README.md
 f0f5ffb1058850994fc0628460844805 *inst/model/schools.txt
 cb5c8a434518b884d450c2867320976c *man/attach.jags.Rd
 f7d2806381459966d900d31a46df8e42 *man/autojags.Rd
-b950cd92225f415bdeea57e003ec9d10 *man/jags.Rd
+68fe2149fef3b97fc34fd8ca04b7b190 *man/jags.Rd
 aa6c6fcdab566cc3a189ba07ff5a8423 *man/jags2bugs.Rd
 dd7972715f34b0925c6895109da53a2d *man/recompile.Rd
 3182b61e64111486844ec8c8f12bdf1e *man/traceplot.Rd

NAMESPACE

@@ -16,6 +16,8 @@ importFrom(abind, "abind")
 
 importFrom(coda, "as.mcmc", "mcmc", "nvar", "varnames", "nchain", "as.mcmc.list", "traceplot")
 
+importFrom(stringr, "str_match")
+
 import(parallel)
 
 importFrom(R2WinBUGS, "attach.bugs",

R/as.bugs.array2.R

@@ -1,5 +1,5 @@
 as.bugs.array2 <- function(sims.array, model.file=NULL, program="jags",
-              DIC=FALSE, DICOutput=NULL, n.iter=NULL, n.burnin=0, n.thin=1)
+              DIC=FALSE, DICOutput=NULL, n.iter=NULL, n.burnin=0, n.thin=1, checkMissing=FALSE)
 {
   ## 'sims.array' is supposed to be a 3-way array with
   # n.sims*n.chains*n.parameters simulations, and
@@ -59,10 +59,9 @@ as.bugs.array2 <- function(sims.array, model.file=NULL, program="jags",
           ## this check fails if you take out a part of the simulations
           ## (for example, you don't want the array to have some of the
           ## parameters) so I took them out.
-
-          ## if (length(long.short[[j]]) != length.short[j])
-          ##   stop(paste("error in parameter", root.short[[j]],
-          ##   "in parameters.to.save"))
+           if (length(long.short[[j]]) != length.short[j]){
+             warning(paste("error/missing in parameter", root.short[[j]],"in parameters.to.save, \n   Be aware of the output results.\n"), noBreaks.=TRUE)
+           }
           indexes.short[[j]] <- as.list(numeric(length.short[j]))
           for (k in 1:length.short[j]){
             indexes.short[[j]][[k]] <- indexes.long[[long.short[[j]][k]]]
@@ -137,13 +136,26 @@ as.bugs.array2 <- function(sims.array, model.file=NULL, program="jags",
       ##fix this list
       #sims.list[[j]] <- aperm(array(sims[, long.short[[j]]], c(n.sims, rev(n.indexes.short[[j]]))), c(1, (dimension.short[j] + 1):2))
       sims.list[[j]] <- array(sims[, long.short[[j]]], c(n.sims, n.indexes.short[[j]]))
+
+      # this is a quick fix to the case where elements in levels are missing, ie empty cells in a parameter matrix 2024.3.31
+      # the code is ugly. need to fix in the future.  Add two hiddent functions below in the end of the page
+      if(checkMissing){
+          missingCell <- .checkEmptyCell(n.indexes.short[[j]], long.short[[j]], parameter.names)
+          if(length(missingCell)>1){
+            for(s in 1:n.sims){
+                sims.list[[j]][s,,][missingCell] <- NA
+            }
+          }
+      }
       #sims.list[[j]] <- sims[, long.short[[j]]]
       summary.mean[[j]] <- array(summary[long.short[[j]],"mean"],n.indexes.short[[j]])
       summary.sd[[j]] <- array(summary[long.short[[j]],"sd"],n.indexes.short[[j]])
       summary.median[[j]] <- array(summary[long.short[[j]],"50%"],n.indexes.short[[j]])
+      
       ##ell: added 025 and 975
 #      summary.025[[j]] <- array(summary[long.short[[j]],"2.5%"],n.indexes.short[[j]])
 #      summary.975[[j]] <- array(summary[long.short[[j]],"97.5%"],n.indexes.short[[j]])
+        
     }
   }
 
@@ -188,3 +200,34 @@ as.bugs.array2 <- function(sims.array, model.file=NULL, program="jags",
   class(all) <- "bugs"
   all
 }
+
+
+.checkEmptyCell <- function(n.indexes.short, long.short, parameter.names){
+    size1 <- prod(n.indexes.short)
+    size2 <- length(long.short)
+    if(size1 > size2){
+        paraNames <- parameter.names[long.short]
+        indicesLst <- lapply(paraNames, .extract_indices)
+        indices <- do.call(rbind, indicesLst)
+        paramMatrix <- matrix(FALSE, nrow = n.indexes.short[1], ncol = n.indexes.short[2])
+        paramMatrix[indices] <- TRUE
+        missingCell <- which(!paramMatrix, arr.ind = TRUE) 
+    }else{
+        missingCell <- NA
+    }
+    return(missingCell)
+}
+
+.extract_indices <- function(parameter.names) {
+  #indices <-  gregexpr("\\d+", parameter.names)[[1]]
+  #indices <- as.numeric(indices)
+  #indices <- gsub("\\d+", "", parameter.names) # Extract only digits
+  #indices <- as.numeric(indices)) # Split into individual digits and convert to numeric
+  indices <- str_match(parameter.names, "\\[(\\d+),(\\d+)\\]")[,-1]
+  indices <- matrix(as.numeric(indices), ncol = 2, byrow = TRUE)
+  #indices <- as.numeric(indices)
+  return(indices)
+}
+
+
+

R/as.mcmc.R

@@ -4,7 +4,7 @@ as.mcmc.rjags <- function (x, ...) {
   x <- x$BUGSoutput
   mclist <- vector("list", x$n.chains)
   mclis <- vector("list", x$n.chains)
-  strt <- x$n.burnin + 1
+  strt <- x$n.burnin + x$n.thin
   end <- x$n.iter
   ord <- order(dimnames(x$sims.array)[[3]])
   for (i in 1:x$n.chains) {

R/jags.R

@@ -13,7 +13,8 @@ jags <- function( data, inits,
                   digits = 5,
                   RNGname = c("Wichmann-Hill", "Marsaglia-Multicarry", "Super-Duper", "Mersenne-Twister"),
                   jags.module = c("glm","dic"),
-                  quiet = FALSE
+                  quiet = FALSE,
+                  checkMissing = FALSE
                   )
 {
   #require( rjags )
@@ -166,15 +167,15 @@ jags <- function( data, inits,
                            thin           = n.thin,
                            by             = refresh,
                            progress.bar   = progress.bar )
-
   fit <- mcmc2bugs( samples,
                     model.file = model.file,
                     program    = "jags",
                     DIC        = DIC,
                     DICOutput  = NULL,
                     n.iter     = n.iter,
                     n.burnin   = n.burnin,
-                    n.thin     = n.thin )
+                    n.thin     = n.thin,
+                    checkMissing = checkMissing )
 
   out <- list( model              = m,
                BUGSoutput         = fit,

R/jags.sims.R

@@ -22,8 +22,7 @@
 
 
 
-jags.sims <- function (parameters.to.save, n.chains, n.iter, n.burnin, n.thin,
-  DIC = TRUE)
+jags.sims <- function (parameters.to.save, n.chains, n.iter, n.burnin, n.thin, DIC = TRUE)
 {
 
   #require(R2WinBUGS)
@@ -46,8 +45,7 @@ jags.sims <- function (parameters.to.save, n.chains, n.iter, n.burnin, n.thin,
   left.bracket.short <- as.vector(regexpr("[[]", parameters.to.save))
   right.bracket.short <- as.vector(regexpr("[]]", parameters.to.save))
   root.short <- ifelse(left.bracket.short == -1, parameters.to.save,
-      substring(parameters.to.save, 1, left.bracket.short -
-          1))
+      substring(parameters.to.save, 1, left.bracket.short - 1))
   dimension.short <- rep(0, n.roots)
   indexes.short <- vector(n.roots, mode = "list")
   n.indexes.short <- vector(n.roots, mode = "list")
@@ -107,8 +105,7 @@ jags.sims <- function (parameters.to.save, n.chains, n.iter, n.burnin, n.thin,
       }
   }
   sims <- sims[sample(n.sims), , drop = FALSE]
-  sims.list <- summary.mean <- summary.sd <- summary.median <- vector(n.roots,
-      mode = "list")
+  sims.list <- summary.mean <- summary.sd <- summary.median <- vector(n.roots,mode = "list")
   names(sims.list) <- names(summary.mean) <- names(summary.sd) <- names(summary.median) <- root.short
   for (j in 1:n.roots) {
       if (length.short[j] == 1) {

R/mcmc2bugs.R

@@ -1,6 +1,6 @@
 
 mcmc2bugs <- function(x, model.file = NULL, program = "", DIC = FALSE, 
-  DICOutput = NULL, n.iter = NULL, n.burnin = 0, n.thin = 1){
+  DICOutput = NULL, n.iter = NULL, n.burnin = 0, n.thin = 1, checkMissing=FALSE){
   parameter.names <- dimnames(x[[1]])[[2]]
   n.keeps <- dim(x[[1]])[1]
   n.chains <- summary(x)[["nchain"]]

README.md

@@ -0,0 +1,2 @@
+# R2jags
+R2jags: Using R to Run 'JAGS'