[r-cran-bayesm] 09/44: Import Upstream version 1.1-1
Andreas Tille
tille at debian.org
Thu Sep 7 11:16:20 UTC 2017
This is an automated email from the git hooks/post-receive script.
tille pushed a commit to branch master
in repository r-cran-bayesm.
commit 1f94f41b3e39f481de1624b355133bb6f0a2fa43
Author: Andreas Tille <tille at debian.org>
Date: Thu Sep 7 13:08:25 2017 +0200
Import Upstream version 1.1-1
---
DESCRIPTION | 6 +++---
R/llmnp.R | 4 ++--
inst/doc/bayesm-manual.pdf | Bin 390357 -> 390397 bytes
man/detailing.Rd | 4 ++--
man/rhierNegbinRw.Rd | 2 +-
src/bayesmc.c | 16 ++++++++++++----
6 files changed, 20 insertions(+), 12 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index 23ca4a5..a8ce985 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
Package: bayesm
-Version: 1.1-0
-Date: 2005-06-10
+Version: 1.1-1
+Date: 2005-07-01
Title:Bayesian Inference for Marketing/Micro-econometrics
Author: Peter Rossi <peter.rossi at ChicagoGsb.edu>,
Rob McCulloch <robert.mcculloch at ChicagoGsb.edu>.
@@ -27,4 +27,4 @@ Description: bayesm covers many important models used
Marketing by Allenby, McCulloch and Rossi.
License: GPL (version 2 or later)
URL: http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html
-Packaged: Fri Jun 10 13:10:33 2005; per
+Packaged: Fri Jul 1 11:33:45 2005; per
diff --git a/R/llmnp.R b/R/llmnp.R
index 6e1c9b2..57975e4 100755
--- a/R/llmnp.R
+++ b/R/llmnp.R
@@ -54,7 +54,7 @@ for (j in 1:pm1) {
trunpt=as.vector(-Aj%*%muj)
Lj=t(chol(Aj%*%Sigma%*%t(Aj)))
# note: rob's routine expects lower triangular root
- logl=logl + sum(log(ghkvec(Lj,trunpt,above,r)))
+ logl=logl + sum(log(ghkvec(Lj,trunpt,above,r)+1.0e-50))
# note: ghkvec does an entire vector of n probs each with different truncation points but the
# same cov matrix.
}
@@ -64,7 +64,7 @@ for (j in 1:pm1) {
trunpt=as.vector(-mu[,y==(pm1+1)])
Lj=t(chol(Sigma))
above=rep(1,pm1)
-logl=logl+sum(log(ghkvec(Lj,trunpt,above,r)))
+logl=logl+sum(log(ghkvec(Lj,trunpt,above,r)+1.0e-50))
return(logl)
}
diff --git a/inst/doc/bayesm-manual.pdf b/inst/doc/bayesm-manual.pdf
index 899bbed..bfcc87b 100755
Binary files a/inst/doc/bayesm-manual.pdf and b/inst/doc/bayesm-manual.pdf differ
diff --git a/man/detailing.Rd b/man/detailing.Rd
index 9c0d19c..f76b99d 100755
--- a/man/detailing.Rd
+++ b/man/detailing.Rd
@@ -4,7 +4,7 @@
\title{ Physician Detailing Data from Manchanda et al (2004)}
\description{
Monthly data on detailing (sales calls) on 1000 physicians. 23 mos of data
- for each Physician. Includes physician covariates. Dependent Variable is the
+ for each Physician. Includes physician covariates. Dependent Variable (\code{scripts}) is the
number of new prescriptions ordered by the physician for the drug detailed.
}
\usage{data(detailing)}
@@ -26,7 +26,7 @@
\ldots\$ mean\_samples: num [1:1000] 0.722 0.491 0.339 3.196 0.348
}
\details{
- generalphy is dummy for if doc is a "general practitioner," specialist is dummy for
+ generalphys is dummy for if doctor is a "general practitioner," specialist is dummy for
if the physician is a specialist in the theraputic class for which the drug is
intended, mean\_samples is the mean number of free drug samples given the doctor
over the sample.
diff --git a/man/rhierNegbinRw.Rd b/man/rhierNegbinRw.Rd
index 1776eb5..999b466 100755
--- a/man/rhierNegbinRw.Rd
+++ b/man/rhierNegbinRw.Rd
@@ -46,7 +46,7 @@ rhierNegbinRw(Data, Prior, Mcmc)
\item{\code{b}}{ Gamma prior parm (def: .1)}
\item{\code{R}}{ number of MCMC draws}
\item{\code{keep}}{ MCMC thinning parm: keep every keepth draw (def: 1)}
- \item{\code{s\_beta}}{ scaling for beta| alpha RW inc cov (def: 2.93/sqrt(nvar)}
+ \item{\code{s\_beta}}{ scaling for beta| alpha RW inc cov (def: 2.93/sqrt(nvar))}
\item{\code{s\_alpha}}{ scaling for alpha | beta RW inc cov (def: 2.93)}
\item{\code{c}}{ fractional likelihood weighting parm (def:2)}
\item{\code{Vbeta0}}{ starting value for Vbeta (def: I)}
diff --git a/src/bayesmc.c b/src/bayesmc.c
index 6d44ce9..73c5833 100755
--- a/src/bayesmc.c
+++ b/src/bayesmc.c
@@ -147,10 +147,11 @@ void ghk_oneside(double *L, double* trunpt, int *above, int *dim, int *n, double
L is lower triangular root of Sigma
random vector is assumed to have zero mean
n is number of draws to use in GHK
+ modified 6/05 by rossi to check arg into qnorm
*/
{
int i,j,k;
- double mu,tpz,u,prod,pa,pb;
+ double mu,tpz,u,prod,pa,pb,arg;
double *z;
z = (double *)R_alloc(*dim,sizeof(double));
GetRNGstate();
@@ -168,7 +169,10 @@ void ghk_oneside(double *L, double* trunpt, int *above, int *dim, int *n, double
}
prod *= pb-pa;
u = unif_rand();
- z[j] = qnorm(u*pb + (1-u)*pa,0.0,1.0,1,0);
+ arg=u*pb+(1.-u)*pa;
+ if(arg > .999999999) arg=.999999999;
+ if(arg < .0000000001) arg=.0000000001;
+ z[j] = qnorm(arg,0.0,1.0,1,0);
}
*res += prod;
}
@@ -181,10 +185,11 @@ void ghk(double *L, double* a, double *b, int *dim, int *n, double *res)
L is lower triangular root of Sigma
random vector is assumed to have zero mean
n is number of draws to use in GHK
+ modified 6/05 by rossi to check arg into qnorm
*/
{
int i,j,k;
- double aa,bb,pa,pb,u,prod,mu;
+ double aa,bb,pa,pb,u,prod,mu,arg;
double *z;
z = (double *)R_alloc(*dim,sizeof(double));
GetRNGstate();
@@ -197,7 +202,10 @@ void ghk(double *L, double* a, double *b, int *dim, int *n, double *res)
pa = pnorm(aa,0.0,1.0,1,0); pb = pnorm(bb,0.0,1.0,1,0);
prod *= pb-pa;
u = unif_rand();
- z[j] = qnorm(u*pb + (1-u)*pa,0.0,1.0,1,0);
+ arg=u*pb+(1.-u)*pa;
+ if(arg > .999999999) arg=.999999999;
+ if(arg < .0000000001) arg=.0000000001;
+ z[j] = qnorm(arg,0.0,1.0,1,0);
}
*res += prod;
}
--
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