Package news (see below for general description of functionality) depmixS4 version 1.3-0 has been released on CRAN. See the NEWS file for an overview of all changes. The most important user-visible changes are: 1) more compact pretty-printing of parameters in print/summary of (dep)mix objects (following lm/glm style of presenting results) 2) some speed improvements in the EM algorithm, most notable in large data/models 3) EM has an optional argument to use the classification likelihood instead of the usual likelihood; this can be useful as a means of starting value generation; use with caution as results are often unstable. Best, happy mixing, Ingmar & Maarten Package general information depmixS4 is a framework for specifying and fitting dependent mixture models, otherwise known as hidden or latent Markov models. Optimization is done with the EM algorithm or optionally with Rdonlp2 when (general linear (in-)equality) constraints on the parameters need to be incorporated. Models can be fitted on (multiple) sets of observations. The response densities for each state may be chosen from the GLM family, or a multinomial. User defined response densities are easy to add; for the latter an example is given for the ex-gauss distribution as well as the multivariate normal distribution. Mixture or latent class (regression) models can also be fitted; these are the limit case in which the length of observed time series is 1 for all cases. _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages