seqHMM

Description

Designed for estimating variants of hidden (latent) Markov models (HMMs), mixture HMMs, and non-homogeneous HMMs (NHMMs) for social sequence data and other categorical time series. Special cases include feedback-augmented NHMMs, Markov models without latent layer, 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 as well as initial, transition and emission probabilities in NHMMs. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and HMMs. For NHMMs, methods for computing average causal effects and marginal state and emission probabilities are available. Models are estimated using maximum likelihood via the EM algorithm or direct numerical maximization with analytical gradients. Documentation is available via several vignettes, and Helske and Helske (2019, <doi:10.18637/jss.v088.i03>). For methodology behind the NHMMs, see Helske (2025, <doi:10.48550/arXiv.2503.16014>).

Downloads

CRAN Check Status

  installed size is 25.6Mb
  sub-directories of 1Mb or more:
    libs  23.3Mb

  installed size is 24.7Mb
  sub-directories of 1Mb or more:
    libs  22.4Mb

Check History

  installed size is 25.6Mb
  sub-directories of 1Mb or more:
    libs  23.3Mb

  installed size is 24.7Mb
  sub-directories of 1Mb or more:
    libs  22.4Mb

Reverse Dependencies (3)

Dependency Network

Version History