[r-cran-mnp] 36/51: Import Upstream version 2.5-4

[Andreas Tille]

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

commit 05f3417a3881118b88f60f2b67d3050b5abd9e50
Author: Andreas Tille <tille at debian.org>
Date:   Fri Sep 8 15:54:57 2017 +0200

    Import Upstream version 2.5-4
---
 DESCRIPTION     | 11 +++++++----
 R/predict.mnp.R |  6 +++---
 2 files changed, 10 insertions(+), 7 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index ba3004d..075496d 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: MNP
-Version: 2.5-3
-Date: 2006-12-04
+Version: 2.5-4
+Date: 2007-05-24
 Title: R Package for Fitting the Multinomial Probit Model
 Author: Kosuke Imai <kimai at princeton.edu>, 
         David A. van Dyk <dvd at uci.edu>. 
@@ -19,9 +19,12 @@ Description: MNP is a publicly available R package that fits the Bayesian
   is based on the efficient marginal data augmentation algorithm that
   is developed by Imai and van Dyk (2005). ``A Bayesian Analysis of
   the Multinomial Probit Model Using the Data Augmentation,'' Journal
-  of Econometrics, Vol. 124, No. 2 (February), pp. 311-334.
+  of Econometrics, Vol. 124, No. 2 (February), pp. 311-334. Detailed
+  examples are given in Imai and van Dyk (2005). ``MNP: R Package for 
+  Fitting the Multinomial Probit Model.'' Journal of Statistical Software,
+  Vol. 14, No. 3 (May), pp. 1-32.
 LazyLoad: yes
 LazyData: yes
 License: GPL (version 2 or later)
 URL: http://imai.princeton.edu/research/MNP.html
-Packaged: Tue Dec  5 15:50:14 2006; kimai
+Packaged: Thu May 24 12:08:24 2007; kimai
diff --git a/R/predict.mnp.R b/R/predict.mnp.R
index 636acee..224f97a 100644
--- a/R/predict.mnp.R
+++ b/R/predict.mnp.R
@@ -8,12 +8,12 @@ predict.mnp <- function(object, newdata = NULL, newdraw = NULL, n.draws = 1,
     stop("Invalid input for `n.draws'.")
 
   p <- object$n.alt
-  if (is.null(newdraw))
+  if (is.null(newdraw)) 
     param <- object$param
   else
     param <- newdraw
-  coef <- coef(object)
-  n.cov <- ncol(coef)
+  n.cov <- ncol(coef(object))
+  coef <- param[,1:n.cov]
   n.mcmc <- nrow(coef)
   cov <- param[,(n.cov+1):ncol(param)]
   

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