[r-cran-mnp] 19/51: Import Upstream version 2.3-5

[Andreas Tille]

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tille pushed a commit to branch master
in repository r-cran-mnp.

commit b0cc21412601eaa8a9d852f618b4d984345470d3
Author: Andreas Tille <tille at debian.org>
Date:   Fri Sep 8 15:54:49 2017 +0200

    Import Upstream version 2.3-5
---
 DESCRIPTION     |  8 ++++----
 R/summary.mnp.R |  5 ++++-
 R/xmatrix.mnp.R | 34 ++++++++++++++++++----------------
 3 files changed, 26 insertions(+), 21 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 404a67c..d76a4e4 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,11 +1,11 @@
 Package: MNP
-Version: 2.3-4
-Date: 2005-09-06
+Version: 2.3-5
+Date: 2005-12-27
 Title: R Package for Fitting the Multinomial Probit Model
 Author: Kosuke Imai <kimai at princeton.edu>, 
         David A. van Dyk <dvd at uci.edu>. 
 Maintainer: Kosuke Imai <kimai at princeton.edu>
-Depends: R (>= 2.0), MASS
+Depends: R (>= 2.1), MASS
 Description: MNP is a publicly available R package that fits the Bayesian
   multinomial probit model via Markov chain Monte Carlo. The
   multinomial probit model is often used to analyze the discrete
@@ -24,4 +24,4 @@ LazyLoad: yes
 LazyData: yes
 License: GPL (version 2 or later)
 URL: http://imai.princeton.edu/research/MNP.html
-Packaged: Tue Sep  6 21:11:41 2005; kimai
+Packaged: Tue Dec 27 02:47:01 2005; kimai
diff --git a/R/summary.mnp.R b/R/summary.mnp.R
index 4a8d5d0..4246357 100644
--- a/R/summary.mnp.R
+++ b/R/summary.mnp.R
@@ -9,10 +9,13 @@ summary.mnp <- function(object, CI=c(2.5, 97.5),...){
                        apply(param, 2, quantile, max(CI)/100)) 
   colnames(param.table) <- c("mean", "std.dev.", paste(min(CI), "%", sep=""),
                              paste(max(CI), "%", sep=""))
+  rownames(param.table) <- colnames(param)
   
   ans <- list(call=object$call, base = object$base, n.alt=p, n.obs=if(is.matrix(object$y))
               nrow(object$y) else length(object$y), n.draws = n.draws,
-              coef.table=param.table[1:n.cov,],
+              coef.table= if(n.cov > 1) param.table[1:n.cov,]
+              else matrix(param.table[1,], nrow=1,
+                          dimnames=list(rownames(param.table)[1], colnames(param.table))),
               cov.table=param.table[(n.cov+1):ncol(param),])  
   class(ans) <- "summary.mnp"
   return(ans)
diff --git a/R/xmatrix.mnp.R b/R/xmatrix.mnp.R
index 97669a7..9760ddd 100644
--- a/R/xmatrix.mnp.R
+++ b/R/xmatrix.mnp.R
@@ -24,25 +24,27 @@ xmatrix.mnp <- function(formula, data = parent.frame(), choiceX=NULL,
   n.cov <- ncol(X)
   
   ## expanding X
-  Xcnames <- colnames(X)
   allvnames <- Xnew <- NULL
-  for (i in 1:n.cov) {
-    Xv <- X[, Xcnames[i]]
-    Xtmp <- varnames <- NULL
-    for (j in 1:n.dim) {
-      allvnames <- c(allvnames, paste(Xcnames[i], ":", if(MoP)
-                                      lev[j] else lev[j+1], sep=""))
-      for (k in 1:n.dim)
-        varnames <- c(varnames, paste(Xcnames[i], ":", if(MoP) lev[j]
-        else lev[j+1], sep=""))
-      tmp <- matrix(0, nrow = n.obs, ncol = n.dim)
-      tmp[, j] <- Xv
-      Xtmp <- cbind(Xtmp, tmp)
+  if (ncol(X) > 0) {
+    Xcnames <- colnames(X)
+    for (i in 1:n.cov) {
+      Xv <- X[, Xcnames[i]]
+      Xtmp <- varnames <- NULL
+      for (j in 1:n.dim) {
+        allvnames <- c(allvnames, paste(Xcnames[i], ":", if(MoP)
+                                        lev[j] else lev[j+1], sep=""))
+        for (k in 1:n.dim)
+          varnames <- c(varnames, paste(Xcnames[i], ":", if(MoP) lev[j]
+          else lev[j+1], sep=""))
+        tmp <- matrix(0, nrow = n.obs, ncol = n.dim)
+        tmp[, j] <- Xv
+        Xtmp <- cbind(Xtmp, tmp)
+      }
+      colnames(Xtmp) <- varnames
+      Xnew <- cbind(Xnew, Xtmp)
     }
-    colnames(Xtmp) <- varnames
-    Xnew <- cbind(Xnew, Xtmp)
   }
-
+  
   ## checking and adding choice-specific variables
   if (!is.null(choiceX)) {
     cX <- eval(choiceX, data)

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