[Depmix-commits] r622 - in pkg/depmix: . R

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Tue Feb 25 09:40:06 CET 2014


Author: ingmarvisser
Date: 2014-02-25 09:40:06 +0100 (Tue, 25 Feb 2014)
New Revision: 622

Modified:
   pkg/depmix/DESCRIPTION
   pkg/depmix/NAMESPACE
   pkg/depmix/R/depmix.R
Log:
Changes to fulfill requirements in R 3.1.0

Modified: pkg/depmix/DESCRIPTION
===================================================================
--- pkg/depmix/DESCRIPTION	2014-02-20 12:23:36 UTC (rev 621)
+++ pkg/depmix/DESCRIPTION	2014-02-25 08:40:06 UTC (rev 622)
@@ -1,10 +1,10 @@
 Package: depmix
 Version: 0.9.11
-Date: 2014-02-19
+Date: 2014-02-20
 Title: Dependent Mixture Models
 Author: Ingmar Visser <i.visser at uva.nl>
 Maintainer: Ingmar Visser <i.visser at uva.nl>
-Depends: R (>= 2.13.1), MASS
+Depends: R (>= 3.0.2), MASS
 Suggests: Rdonlp2
 Description: Fit (multigroup) mixtures of latent Markov models on mixed categorical and continuous (timeseries) data 
 License: GPL-3
\ No newline at end of file

Modified: pkg/depmix/NAMESPACE
===================================================================
--- pkg/depmix/NAMESPACE	2014-02-20 12:23:36 UTC (rev 621)
+++ pkg/depmix/NAMESPACE	2014-02-25 08:40:06 UTC (rev 622)
@@ -1,5 +1,7 @@
 useDynLib(depmix)
 
+import(MASS)
+
 export(dmm,mgdmm,fitdmm,mixdmm,loglike,oneliner,bootstrap,posterior,
 	generate,lca,ntimes,itemtypes,dname,replicates,ncov,inames,
 	nitems,ind,markovdata)

Modified: pkg/depmix/R/depmix.R
===================================================================
--- pkg/depmix/R/depmix.R	2014-02-20 12:23:36 UTC (rev 621)
+++ pkg/depmix/R/depmix.R	2014-02-25 08:40:06 UTC (rev 622)
@@ -14,6 +14,8 @@
 #                                 #
 ###################################
 
+if(getRversion() >= "2.15.1")  utils::globalVariables(c("donlp2", "donlp2Control"))
+
 fitdmm <- function(dat,dmm,printlevel=1,poster=TRUE,tdcov=0,ses=TRUE,method="optim",vfactor=15,der=1,iterlim=100,kmst=!dmm$st,kmrep=5,postst=FALSE) { 
 	mod=dmm #keep copy of the original model
 ## create good starting values if not provdided



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