[Depmix-commits] r616 - in pkg/depmixS4: . vignettes

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Tue Feb 4 12:11:48 CET 2014 

Author: ingmarvisser
Date: 2014-02-04 12:11:47 +0100 (Tue, 04 Feb 2014)
New Revision: 616

Removed:
   pkg/depmixS4/vignettes/depmixS4.pdf
Modified:
   pkg/depmixS4/DESCRIPTION
   pkg/depmixS4/NEWS
   pkg/depmixS4/vignettes/depmixS4.Rnw
Log:
Minor changes to conform to upcoming changes in R 3.1.0

Modified: pkg/depmixS4/DESCRIPTION
===================================================================
--- pkg/depmixS4/DESCRIPTION	2014-02-03 22:02:05 UTC (rev 615)
+++ pkg/depmixS4/DESCRIPTION	2014-02-04 11:11:47 UTC (rev 616)
@@ -1,6 +1,6 @@
 Package: depmixS4
 Version: 1.3-2
-Date: 2014-02-03
+Date: 2014-02-04
 Title: Dependent Mixture Models - Hidden Markov Models of GLMs and Other Distributions in S4
 Author: Ingmar Visser <i.visser at uva.nl>, Maarten Speekenbrink <m.speekenbrink at ucl.ac.uk>
 Maintainer: Ingmar Visser <i.visser at uva.nl>

Modified: pkg/depmixS4/NEWS
===================================================================
--- pkg/depmixS4/NEWS	2014-02-03 22:02:05 UTC (rev 615)
+++ pkg/depmixS4/NEWS	2014-02-04 11:11:47 UTC (rev 616)
@@ -1,3 +1,8 @@
+Changes in depmixS4 version 1.3-2
+
+  o Removed partial matching argument in call to check.attributes for 
+    compatibility with R release 3.1.0. 
+
 Changes in depmixS4 version 1.3-1
 
 Major changes
@@ -4,21 +9,21 @@
 
   o Fixed a bug in the fit function of (dep-)mix objects; upper and lower 
     bounds of general linear contraints were not passed to the optimization 
-		routines when any of the bounds was zero; in that case, all bounds were 
-		set to zero. Thanks to Vincent Miele for bringing this to my 
-		attention. 
+	routines when any of the bounds was zero; in that case, all bounds were 
+	set to zero. Thanks to Vincent Miele for bringing this to my 
+	attention. 
 
 Minor changes
 
   o Added a reference to Giudici et al (2000) in the vignette in the 
-	  section on likelihood ratio testing which fits better with the 
-		procedure that is implemented. Thanks to Jan Bulla for probing us 
-		about the vignette text there. 	  
+	section on likelihood ratio testing which fits better with the 
+	procedure that is implemented. Thanks to Jan Bulla for probing us 
+	about the vignette text there. 	  
 
-	o Added a conditional to set the log likelihood of a model to a value
-	  just above the starting value (i.e. the values before iterations start)
-	  when the logl functions returns Infinite (which may sometimes occur when
-	  parameters are set outside their boundaries).
+  o Added a conditional to set the log likelihood of a model to a value
+	just above the starting value (i.e. the values before iterations start)
+	when the logl functions returns Infinite (which may sometimes occur when
+	parameters are set outside their boundaries).
 
 
 Changes in depmixS4 version 1.3-0
@@ -26,26 +31,26 @@
 Major changes
 
   o The EM algorithm has gained an extra argument 'classification',
-	  passed from the 'fit' function using argument 'emcontrol', to allow a
- 	  choice between maximising the regular (classification="soft", the
-	  default) or classification (classification="hard") likelihood. 
-	  WARNING: using the classification likelihood combined with random 
-	  starting values may easily lead to unstable results; use with 
-	  caution. 
+	passed from the 'fit' function using argument 'emcontrol', to allow a
+ 	choice between maximising the regular (classification="soft", the
+	default) or classification (classification="hard") likelihood. 
+	WARNING: using the classification likelihood combined with random 
+	starting values may easily lead to unstable results; use with 
+	caution. 
 
   o Parameters are now given proper names, following the glm() scheme
   	(e.g. '(Intercept)', 'x1', et cetera); with this, the show and summary
-	  methods have changed considerably and now produce more compact and more
-	  readable output.  The summary method (for both fitted and unfitted
-	  models) now has an argument 'compact' (TRUE by default) that controls
-	  the presentation of the repsonse model parameters.  The prior and
-	  transition models are now presented more compactly when there are no
-	  covariates.
+	methods have changed considerably and now produce more compact and more
+	readable output.  The summary method (for both fitted and unfitted
+	models) now has an argument 'compact' (TRUE by default) that controls
+	the presentation of the repsonse model parameters.  The prior and
+	transition models are now presented more compactly when there are no
+	covariates.
 	
   o The fit function has gained two arguments: solnpcntrl and donlpcntrl 
     which can be used to fine tune optimization using packages Rsolnp and 
-	  Rdonlp2; the latter is not on CRAN, and the version that depmixS4 is 
-	  compatible with is from r-forge (note the licence from the package). 
+	Rdonlp2; the latter is not on CRAN, and the version that depmixS4 is 
+	compatible with is from r-forge (note the licence from the package). 
 
   o The EM algorithm is now more memory efficient and hence faster, 
     most notably for large models and/or data; thanks to Robert McGehee
@@ -61,12 +66,12 @@
     the show method for these models.  
 
   o Added function getmodel(object) to select submodels of a full mix or 
-	  depmix model, eg to use in deriving predictions, getting at parameter 
-	  values, et cetera. 
+	depmix model, eg to use in deriving predictions, getting at parameter 
+	values, et cetera. 
 
   o Small parameter values in multinomial response models and the initial
-	  probabilities and transition models (with identity link) are now set to
-	  zero to speed-up convergence.  Current threshold is 1e-6. 
+	probabilities and transition models (with identity link) are now set to
+	zero to speed-up convergence.  Current threshold is 1e-6. 
 
 Changes in depmixS4 version 1.2-2
 
@@ -74,7 +79,7 @@
 
   o Fixed a bug in the fit method of depmix models: linear inequality 
     constraints were not passed on to rsolnp (thanks to Peiming Wang for 
-	  bringing this to my attention). 
+	bringing this to my attention). 
 
 Changes in depmixS4 version 1.2-1
 
@@ -85,7 +90,7 @@
 Major changes
   
   o Missing values for responses are now allowed. Note that missing values 
-	  in covariates will cause errors. 
+	in covariates will cause errors. 
     
 Changes in depmixS4 version 1.1-0
   
@@ -135,8 +140,8 @@
 
   o Fixed a bug in simulation of gaussian response model, which was 
     returning NaNs due to an error in assignment of the sd parameter
-   (introduced in version x). Thanks to Jeffrey Arnold for reporting
-   this (bug #1365). 
+    (introduced in version x). Thanks to Jeffrey Arnold for reporting
+	this (bug #1365). 
 
 Changes in depmixS4 version 1.0-3
 

Modified: pkg/depmixS4/vignettes/depmixS4.Rnw
===================================================================
--- pkg/depmixS4/vignettes/depmixS4.Rnw	2014-02-03 22:02:05 UTC (rev 615)
+++ pkg/depmixS4/vignettes/depmixS4.Rnw	2014-02-04 11:11:47 UTC (rev 616)
@@ -25,12 +25,13 @@
 \Abstract{	
 
 	This introduction to the \proglang{R} package \pkg{depmixS4} is a
-	(slightly) modified version of \cite{Visser2010},
-	published in the \emph{Journal of Statistical Software}.  Please
-	refer to that article when using \pkg{depmixS4}.  The current
-	version is 1.3-0; the version history and changes can be found in
-	the NEWS file of the package. Below, the major versions are listed 
-	along with the most noteworthy changes. 
+	(slightly) modified version of \cite{Visser2010}, published in the
+	\emph{Journal of Statistical Software}.  Please refer to that
+	article when using \pkg{depmixS4}.  The current version is
+	\Sexpr{packageDescription("depmixS4")$Version}; the version
+	history and changes can be found in the NEWS file of the package.
+	Below, the major versions are listed along with the most
+	noteworthy changes.
 
 	\pkg{depmixS4} implements a general framework for defining and
 	estimating dependent mixture models in the \proglang{R} programming
@@ -300,11 +301,12 @@
 
 \subsection{Parameter estimation}
 
-Parameters are estimated in \pkg{depmixS4} using the expectation-maximization (EM) algorithm or
-through the use of a general Newton-Raphson optimizer.  In the EM
-algorithm, parameters are estimated by iteratively maximizing the
-expected joint log-likelihood of the parameters given the observations and
-states.  Let $\greekv{\theta} = (\greekv{\theta}_1,
+Parameters are estimated in \pkg{depmixS4} using the
+expectation-maximization (EM) algorithm or through the use of a
+general Newton-Raphson optimizer.  In the EM algorithm, parameters are
+estimated by iteratively maximizing the expected joint log-likelihood
+of the parameters given the observations and states.  Let
+$\greekv{\theta} = (\greekv{\theta}_1,
 \greekv{\theta}_2,\greekv{\theta}_3)$ be the general parameter vector
 consisting of three subvectors with parameters for the prior model,
 transition model, and response models respectively.  The joint

Deleted: pkg/depmixS4/vignettes/depmixS4.pdf
===================================================================
(Binary files differ)

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