[Depmix-commits] r606 - tags/release-1.3-0
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Sep 19 10:50:28 CEST 2013
Author: ingmarvisser
Date: 2013-09-19 10:50:27 +0200 (Thu, 19 Sep 2013)
New Revision: 606
Removed:
tags/release-1.3-0/DESCRIPTION
tags/release-1.3-0/NAMESPACE
tags/release-1.3-0/NEWS
tags/release-1.3-0/README
Log:
More files to remove
Deleted: tags/release-1.3-0/DESCRIPTION
===================================================================
--- tags/release-1.3-0/DESCRIPTION 2013-09-19 08:50:01 UTC (rev 605)
+++ tags/release-1.3-0/DESCRIPTION 2013-09-19 08:50:27 UTC (rev 606)
@@ -1,13 +0,0 @@
-Package: depmixS4
-Version: 1.3-0
-Date: 2013-09-17
-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/
Deleted: tags/release-1.3-0/NAMESPACE
===================================================================
--- tags/release-1.3-0/NAMESPACE 2013-09-19 08:50:01 UTC (rev 605)
+++ tags/release-1.3-0/NAMESPACE 2013-09-19 08:50:27 UTC (rev 606)
@@ -1,62 +0,0 @@
-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
-)
Deleted: tags/release-1.3-0/NEWS
===================================================================
--- tags/release-1.3-0/NEWS 2013-09-19 08:50:01 UTC (rev 605)
+++ tags/release-1.3-0/NEWS 2013-09-19 08:50:27 UTC (rev 606)
@@ -1,280 +0,0 @@
-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).
-
-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
Deleted: tags/release-1.3-0/README
===================================================================
--- tags/release-1.3-0/README 2013-09-19 08:50:01 UTC (rev 605)
+++ tags/release-1.3-0/README 2013-09-19 08:50:27 UTC (rev 606)
@@ -1,53 +0,0 @@
-
-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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