[r-cran-mnp] 49/51: Import Upstream version 2.6-4
Andreas Tille
tille at debian.org
Fri Sep 8 14:14:49 UTC 2017
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tille pushed a commit to branch master
in repository r-cran-mnp.
commit a084a9063ca5efd9fee46faf6ce260c4af036c26
Author: Andreas Tille <tille at debian.org>
Date: Fri Sep 8 15:55:26 2017 +0200
Import Upstream version 2.6-4
---
DESCRIPTION | 49 ++++++++++++++++++++++++++-----------------------
MD5 | 10 +++++-----
MNP.pdf | Bin 3497615 -> 3497571 bytes
R/mnp.R | 4 ++--
R/onAttach.R | 7 ++++---
R/xmatrix.mnp.R | 2 +-
6 files changed, 38 insertions(+), 34 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index d031897..4fc7f12 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,32 +1,35 @@
Package: MNP
-Version: 2.6-3
-Date: 2011-12-06
+Version: 2.6-4
+Date: 2013-06-09
Title: R Package for Fitting the Multinomial Probit Model
-Author: Kosuke Imai <kimai at princeton.edu>,
- David A. van Dyk <dvd at uci.edu>.
+Author: Kosuke Imai <kimai at princeton.edu>, David A. van Dyk
+ <dvd at uci.edu>.
Maintainer: Kosuke Imai <kimai at princeton.edu>
Depends: R (>= 2.1), MASS, utils
-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
- choices made by individuals recorded in survey data. Examples where
- the multinomial probit model may be useful include the analysis of
- product choice by consumers in market research and the analysis of
- candidate or party choice by voters in electoral studies. The MNP
- software can also fit the model with different choice sets for each
- individual, and complete or partial individual choice orderings of
- the available alternatives from the choice set. The estimation
- 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. 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.
+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 choices made by individuals recorded in survey data.
+ Examples where the multinomial probit model may be useful
+ include the analysis of product choice by consumers in market
+ research and the analysis of candidate or party choice by
+ voters in electoral studies. The MNP software can also fit the
+ model with different choice sets for each individual, and
+ complete or partial individual choice orderings of the
+ available alternatives from the choice set. The estimation 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. 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 (>= 2)
URL: http://imai.princeton.edu/software/MNP.html
-Packaged: 2011-12-07 01:33:35 UTC; kimai
+Packaged: 2013-06-09 17:45:34 UTC; kimai
+NeedsCompilation: yes
Repository: CRAN
-Date/Publication: 2011-12-07 10:13:42
+Date/Publication: 2013-06-09 20:16:42
diff --git a/MD5 b/MD5
index 1b6b0a4..c97bfc4 100644
--- a/MD5
+++ b/MD5
@@ -1,15 +1,15 @@
-df4b5179b39eb6c39808e112de25d26f *DESCRIPTION
-9b26f9253e17855e62ec571ecf8dc379 *MNP.pdf
+7c923c417c32a5d1a9b62db575670762 *DESCRIPTION
+e5dbaa21eb5db71bef6d103cc66a5896 *MNP.pdf
d30ea84d5abbc3f5323c8f384954ee69 *NAMESPACE
97a7c7aa155788b4a62bdd3e3c02fab0 *R/coef.mnp.R
127b786d97aa185eac38721c23aa2f90 *R/cov.mnp.R
-3a6ed5aa696b22d8c19fc5071bf51554 *R/mnp.R
-5c809a499b486e0bd0a152b1d313814d *R/onAttach.R
+3f7ce384c42415e3e5fe81e7c74143aa *R/mnp.R
+5e40e20eb515081275508f808be52c3e *R/onAttach.R
88edaa6559267b5e85bc8bba9b291b97 *R/predict.mnp.R
e822d2e847f5daf2922a019fa2a4c491 *R/print.mnp.R
a6f93ff28505296a3b6ed5c67a0286ab *R/print.summary.mnp.R
a954cf57cf2e252b7837ac4739d87eab *R/summary.mnp.R
-67068018b650fa86614517cf94c81d2f *R/xmatrix.mnp.R
+cfdc76deb4c1e71bdb9422bf9f2cecd9 *R/xmatrix.mnp.R
f594a4e2db80f456c9dee49d5f9efa6c *R/ymatrix.mnp.R
c342e6c52a792ec58aac9efa0be703ae *data/detergent.txt.gz
bb1181c0a078518436a2a7c9ee5594a9 *data/japan.txt.gz
diff --git a/MNP.pdf b/MNP.pdf
index 764fbd0..1868b5a 100644
Binary files a/MNP.pdf and b/MNP.pdf differ
diff --git a/R/mnp.R b/R/mnp.R
index 545f12d..c924c2f 100644
--- a/R/mnp.R
+++ b/R/mnp.R
@@ -4,7 +4,7 @@ mnp <- function(formula, data = parent.frame(), choiceX = NULL,
p.df = n.dim+1, p.scale = 1, coef.start = 0,
cov.start = 1, burnin = 0, thin = 0, verbose = FALSE) {
call <- match.call()
- mf <- match.call(expand = FALSE)
+ mf <- match.call(expand.dots = FALSE)
mf$choiceX <- mf$cXnames <- mf$base <- mf$n.draws <- mf$latent <-
mf$p.var <- mf$p.df <- mf$p.scale <- mf$coef.start <- mf$invcdf <-
mf$trace <- mf$cov.start <- mf$verbose <- mf$burnin <- mf$thin <- NULL
@@ -164,7 +164,7 @@ mnp <- function(formula, data = parent.frame(), choiceX = NULL,
if (latent) {
W <- array(as.vector(t(param[,(n.par-n.dim*n.obs+1):n.par])),
dim = c(n.dim, n.obs, floor((n.draws-burnin)/keep)),
- dimnames = list(lev[-1], rownames(Y), NULL))
+ dimnames = list(lev[!(lev %in% base)], rownames(Y), NULL))
param <- param[,1:(n.par-n.dim*n.obs)]
}
else
diff --git a/R/onAttach.R b/R/onAttach.R
index 84aff8f..e21b04a 100644
--- a/R/onAttach.R
+++ b/R/onAttach.R
@@ -1,6 +1,7 @@
".onAttach" <- function(lib, pkg) {
mylib <- dirname(system.file(package = pkg))
- title <- packageDescription(pkg, lib = mylib)$Title
- ver <- packageDescription(pkg, lib = mylib)$Version
- packageStartupMessage(paste(pkg, ": ", title, "\nVersion: ", ver, "\n", sep=""))
+ title <- packageDescription(pkg, lib.loc = mylib)$Title
+ ver <- packageDescription(pkg, lib.loc = mylib)$Version
+ author <- packageDescription(pkg, lib.loc = mylib)$Author
+ packageStartupMessage(pkg, ": ", title, "\nVersion: ", ver, "\nAuthors: ", author, "\n")
}
diff --git a/R/xmatrix.mnp.R b/R/xmatrix.mnp.R
index 9760ddd..53d6970 100644
--- a/R/xmatrix.mnp.R
+++ b/R/xmatrix.mnp.R
@@ -2,7 +2,7 @@ xmatrix.mnp <- function(formula, data = parent.frame(), choiceX=NULL,
cXnames=NULL, base=NULL, n.dim, lev,
MoP=FALSE, verbose=FALSE, extra=FALSE) {
call <- match.call()
- mf <- match.call(expand = FALSE)
+ mf <- match.call(expand.dots = FALSE)
mf$choiceX <- mf$cXnames <- mf$base <- mf$n.dim <- mf$lev <-
mf$MoP <- mf$verbose <- mf$extra <- NULL
--
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