[Depmix-commits] r607 - tags/release-1.3-0
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Sep 19 10:51:28 CEST 2013
Author: ingmarvisser
Date: 2013-09-19 10:51:27 +0200 (Thu, 19 Sep 2013)
New Revision: 607
Added:
tags/release-1.3-0/DESCRIPTION
tags/release-1.3-0/NAMESPACE
tags/release-1.3-0/NEWS
tags/release-1.3-0/R/
tags/release-1.3-0/README
tags/release-1.3-0/data/
tags/release-1.3-0/inst/
tags/release-1.3-0/man/
tags/release-1.3-0/src/
tags/release-1.3-0/tests/
tags/release-1.3-0/vignettes/
Log:
Tag copy of release 1.3-0
Copied: tags/release-1.3-0/DESCRIPTION (from rev 606, pkg/depmixS4/DESCRIPTION)
===================================================================
--- tags/release-1.3-0/DESCRIPTION (rev 0)
+++ tags/release-1.3-0/DESCRIPTION 2013-09-19 08:51:27 UTC (rev 607)
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+Package: depmixS4
+Version: 1.3-0
+Date: 2013-09-18
+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>
+Depends: R (>= 3.0.1), nnet, MASS, Rsolnp
+Imports: stats, stats4, methods
+Suggests: gamlss, gamlss.dist
+Description: Fit latent (hidden) Markov models on mixed categorical and continuous (timeseries)
+ data, otherwise known as dependent mixture models
+License: GPL (>=2)
+URL: http://depmix.r-forge.r-project.org/
Copied: tags/release-1.3-0/NAMESPACE (from rev 606, pkg/depmixS4/NAMESPACE)
===================================================================
--- tags/release-1.3-0/NAMESPACE (rev 0)
+++ tags/release-1.3-0/NAMESPACE 2013-09-19 08:51:27 UTC (rev 607)
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+import(methods, MASS, nnet, Rsolnp)
+
+importFrom(stats, predict, simulate)
+
+importFrom(stats4, AIC, BIC, logLik, nobs, summary)
+
+export(
+ makeDepmix,
+ makeMix,
+ lystig,
+ fb,
+ forwardbackward,
+ MVNresponse,
+ llratio,
+ multinomial,
+ em,
+ em.control,
+ viterbi,
+ mlogit,
+ logLik
+)
+
+exportClasses(
+ depmix,
+ depmix.sim,
+ mix,
+ mix.sim,
+ depmix.fitted,
+ mix.fitted,
+ response,
+ GLMresponse,
+ MVNresponse,
+ transInit
+)
+
+exportMethods(
+ fit,
+ getConstraints,
+ npar,
+ freepars,
+ nlin,
+ getdf,
+ nobs,
+ nresp,
+ ntimes,
+ nstates,
+ depmix,
+ mix,
+ posterior,
+ GLMresponse,
+ MVNresponse,
+ transInit,
+ setpars,
+ getpars,
+ predict,
+ dens,
+ show,
+ simulate,
+ summary,
+ logLik,
+ getmodel
+)
Copied: tags/release-1.3-0/NEWS (from rev 606, pkg/depmixS4/NEWS)
===================================================================
--- tags/release-1.3-0/NEWS (rev 0)
+++ tags/release-1.3-0/NEWS 2013-09-19 08:51:27 UTC (rev 607)
@@ -0,0 +1,284 @@
+Changes in depmixS4 version 1.3-0
+
+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.
+
+ 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.
+
+ 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).
+
+ o The EM algorithm is now more memory efficient and hence faster,
+ most notably for large models and/or data; thanks to Robert McGehee
+ for generously providing these code enhancements.
+
+Minor changes
+
+ o Binomial models now treat factors in the same way as glm(); that is
+ the first level of a factor is treated as a failure, and the remaining
+ levels as successes.
+
+ o Un-fitted models now also have a summary method, which is identical to
+ 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.
+
+ 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.
+
+Changes in depmixS4 version 1.2-2
+
+ o Changed class assignment of depmix.fitted object using as().
+
+ 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).
+
+Changes in depmixS4 version 1.2-1
+
+ o Fixed a bug in handling of missing values for mix models
+
+Changes in depmixS4 version 1.2-0
+
+Major changes
+
+ o Missing values for responses are now allowed. Note that missing values
+ in covariates will cause errors.
+
+Changes in depmixS4 version 1.1-0
+
+ Major changes
+
+ o The main loop computing the forward and backward variables for use in
+ the EM algorithm is now implemented in C. Depending on model specifics
+ this results in a 2-4 fold speed increase when fitting models.
+
+ o The Changes for each release (in the NEWS file) is now split into two
+ sections: Major and Minor changes.
+
+ o Added several examples on the ?responses page (Poisson change point
+ model, similar model with a single multinomial response) and the
+ ?depmix page (model for S&P 500 returns; thanks to Chen Haibo for
+ sending this).
+
+ Minor changes
+
+ o Corrected a typo in the vignette in Equation 1; the first occurrence
+ of S read S_t instead of S_1 (thanks to Peng Yu for reporting this).
+
+ o Added a sensible error message when the data contains missings (depmixS4
+ can not handle missing data yet).
+
+ o Fixed a bug in the relative stopping criterion for EM (which resulted
+ in immediate indication of convergence for positive log likelihoods;
+ thanks to Chen Haibo for sending the S&P 500 example which brought out
+ this problem).
+
+ o Function forwardbackward now has a useC argument to determine whether
+ C code is used, the default, or not (the R code is mostly left in place
+ for easy debugging).
+
+ o Added a fix for models without covariates/intercepts. In responseGLM
+ and responseMVN the function setpars now exits when length(value) == 0.
+ In setpars.depmix, a check is added whether npar > 0.
+
+Changes in depmixS4 version 1.0-4
+
+ o Added examples of the use of ntimes argument on ?depmix and ?fit
+ help pages using the ?speed data (which now has the full reference
+ to the accompanying publication).
+
+ o Using nobs generic from stats/stats4 rather than defining them
+ anew (which gave clashes with other packages that did the same).
+
+ 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).
+
+Changes in depmixS4 version 1.0-3
+
+ o Using AIC/BIC/logLik generics from stats/stats4 rather than
+ defining them anew (which gave clashes with other packages that did
+ the same).
+
+Changes in depmixS4 version 1.0-2
+
+ o fixed a bug in simulation of binomial response model data (the response
+ consists of the number of successes, and the number of failures; in
+ simulation, the number of failures was an exact copy of the number of
+ successes).
+
+ o added a meaningful error message in the EM algorithm for lca/mixture
+ models in case the initial log likelihood is NA (thanks to Matthias
+ Ihrke for pointing this out).
+
+Changes in depmixS4 version 1.0-1
+
+ o minor changes in documentation to conform to R 2.12.0 standards.
+
+ o fixed a bug concerning random start values (the argument to specify
+ this was not passed to the EM algorithm and hence was completely
+ ineffective ...).
+
+ o changed the emcontrol argument to the fit function; it now calls
+ a function em.control which returns the list of control parameters, which
+ now also includes maxit, the max number of iterations of the EM algorithm.
+ This makes future additions to EM control parameters easier.
+
+ o random parameter initialization is now the default when using EM
+ to fit models.
+
+ o fixed a bug in multinomial models with n>1; the parameters are now
+ normalized such that they sum to unity (this bug was introduced in
+ version 0.9-0 in multinomial models with identity link).
+
+ o added an error message for multinomial response models with n>1 and
+ link='mlogit' as this case is not handled; n>1 multinomial can use the
+ 'identity' link function.
+
+Changes in depmixS4 version 1.0-0
+
+ o added a vignette to the package and upped the version number 1.0-0 to
+ celebrate publication in the Journal of Statistical Software.
+
+Changes in depmixS4 version 0.9-1
+
+ o fixed a bug in setting the lower and upper bounds for GLMresponse
+ models (the number of bounds was wrong for models with covariates/
+ predictors; these bounds are only used in constrained optimization in
+ which case they produced an error immediately; in EM optimization these
+ bounds are not used).
+
+Changes in depmixS4 version 0.9-0
+
+ o added optimization using Rsolnp, which can be invoked by using
+ method="rsolnp" in calling fit on (dep-)mix objects. Note that
+ this is meant for fitting models with additional constraints.
+ Method="rsolnp" is now the default when fitting constrained
+ models, method="donlp" is still supported.
+
+ o added documentation for control arguments that can be passed to
+ em algorithm, particularly for controlling the tolerance in
+ optimization.
+
+ o added multinomial models with identity link for transition and prior
+ probabilities. These are now the default when no covariates are
+ present.
+
+ o added bounds and constraints for multinomial identity models such
+ that these constraints are satisfied when fitting models with
+ method="rsolnp" or "donlp". Also, variance and sd parameters in
+ gaussian and multivariate normal models are given bounds to prevent
+ warnings and errors in optimization of such models using rsolnp or
+ donlp.
+
+ o added option to generate starting values as part of the EM
+ algorithm.
+
+ o fixed a bug in multinomial response models with n>1; the response for
+ these models can be specified as a k-column matrix with the number of
+ observed responses for each category; the loglikelihood for these
+ models in which there was more than 1 observation per row was
+ incorrect; note that such models may lead to some numerical
+ instabilities when n is large.
+
+Changes in depmixS4 version 0.3-0
+
+ o added multinomial response function with identity link (no covariates
+ allowed in such a model); useful when (many) boundary values occur;
+ currently no constraints are used for such models, and hence only EM
+ can be used for optimization, or alternatively, if and when Rdonlp2
+ is used, sum constraints need to be added when fitting the model.
+ See ?GLMresponse for details.
+
+ o added an example of how to specify a model with multivariate normal
+ responses (and fixed a bug in MVNresponse that prevented such models
+ from being specified in the first place). See ?makeDepmix for an
+ example.
+
+Changes in depmixS4 version 0.2-2
+
+ o fixed a warning produced when specifying conrows.upper and .lower in
+ the fit function
+
+ o added error message in case the initial log likelihood is infeasible
+
+ o fixed a bug in the fit function for multinomial response models with
+ covariates (thanks to Gilles Dutilh for spotting this)
+
+Changes in depmixS4 version 0.2-1
+
+ o fixed a bug in the Viterbi algorithm used to compute posterior states
+ (this bug was introduced in version 0.2-0)
+
+ o restructured test files somewhat
+
+ o fixed a bug in the use of the conrows argument in the fit function (a
+ missing drop=FALSE statement)
+
+ o updated help files for mix classes
+
+ o fixed a bug in setting the starting values of regression coefficients in
+ prior and transInit models with covariates (thanks to Verena Schmittmann
+ for reporting this)
+
+ o added newx argument to predict function of transInit objects, to be used
+ for predicting probabilities depending on covariates (useful in eg plotting
+ transition probabilities as function of a covariate)
+
+ o added example of the use of conrows argument in fitting functions and other
+ minor updates in documentation
+
+Changes in depmixS4 version 0.2-0
+
+ o restructured R and Rd (help) files; added depmixS4 help with a short
+ overview of the package and links to appropriate help files
+
+ o added function 'simulate' to generate new data from a (fitted) model
+
+ o added function 'forwardbackward' to access the forward and backward
+ variables as well as the smoothed transition and state variables
+
+ o added new glm distributions: gamma, poisson
+
+ o added multivariate normal distribution
+
+ o freepars now works correctly on both depmix and depmix.fitted objects
+
+ o added function 'nlin' to compute the number of linear constraints in
+ a fitted model object
+
+ o added mix class for mixture and latent class models; the depmix class
+ extends this mix class and adds a transition model to it
+
+ o added help file for makeDepmix to provide full control in specifying
+ models
+
+ o minor changes to make depmixS4 compatible with R 2.7.1
+
+
+Changes in depmixS4 version 0.1-1
+
+ o adjusted for R 2.7.0
+
+First version released on CRAN: 0.1-0
Copied: tags/release-1.3-0/README (from rev 606, pkg/depmixS4/README)
===================================================================
--- tags/release-1.3-0/README (rev 0)
+++ tags/release-1.3-0/README 2013-09-19 08:51:27 UTC (rev 607)
@@ -0,0 +1,53 @@
+
+FITTING HIDDEN MARKOV MODELS IN R
+
+depmixS4 provides a framework for specifying and fitting hidden Markov
+models. The observation densities use an interface to the glm
+distributions, most of which are now implemented. The vignette that
+accompanies the package has a table with available response distributions
+Besides these, observations can be modelled using the multinomial
+distribution with identity or logistic link function. The latter provides
+functionality for multinomial logistic responses with covariates. The
+transition matrix and the initial state probabilities are also modeled as
+multinomial logistics (or multinomials with identity link, which is the
+default when no covariates are present) with the possibility of including
+covariates.
+
+Optimization is by default done using the EM algorithm. When (linear)
+constraints are included, package Rsolnp is used for optimization (there is
+also support for using Rdonlp2 as optimizer, see USING RDONLP2 below). New
+response distributions can be added by extending the response-class and
+writing appropriate methods for it (dens, and getpars and setpars); an
+example of this is provided on the ?makeDepmix help page. depmixS4 also
+fits latent class and mixture models, see ?mix for an example.
+
+The latest development versions of depmixS4 (and depmix) can be found at:
+https://r-forge.r-project.org/projects/depmix/
+
+
+FOR DEPMIX USERS
+
+depmixS4 is a completely new implementation of the depmix package using S4
+classes. Model specification now uses formulae and family objects,
+familiar from the lm and glm functions. Moreover, the transition matrix
+and the initial state probabilities (as well as multinomial responses) are
+now modeled as multinomial logistics with a baseline. Specification of
+linear constraints uses the same mechanism as was used in depmix, with the
+only difference that constraints are passed as arguments to the fit
+function rather than the model specification function. See the help files
+for further details. NOTE: most of the functionality of depmix is now
+also provided in depmixS4; in the future therefor I may stop updating
+depmix.
+
+
+USING RDONLP2
+
+Optimization of models with (general) linear (in-)equality constraint is
+done using Rsolnp (available from CRAN). Optionally the Rdonlp2 package
+can be used; Rdonlp2 was written by Ryuichi Tamura(ry.tamura @ gmail.com),
+and can currently be installed using:
+
+install.packages("Rdonlp2", repos= c("http://R-Forge.R-project.org", getOption("repos")))
+
+Note the licence information which says, among other things: "The free use
+of donlp2 and parts of it is restricted for research purposes ..."
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