seqHMM: Hidden Markov Models for Life Sequences and Other Multivariate, Multichannel Categorical Time Series
Version 1.0.7

Designed for fitting hidden (latent) Markov models and mixture hidden Markov models for social sequence data and other categorical time series. Also some more restricted versions of these type of models are available: Markov models, mixture Markov models, and latent class models. The package supports models for one or multiple subjects with one or multiple parallel sequences (channels). External covariates can be added to explain cluster membership in mixture models. The package provides functions for evaluating and comparing models, as well as functions for easy plotting of multichannel sequence data and hidden Markov models. Models are estimated using maximum likelihood via the EM algorithm and/or direct numerical maximization with analytical gradients. All main algorithms are written in C++ with support for parallel computation.

Package details

AuthorJouni Helske, Satu Helske
Date of publication2017-04-04 17:17:35 UTC
MaintainerJouni Helske <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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seqHMM documentation built on May 30, 2017, 8:13 a.m.