Package: seqHMM
Title: Hidden Markov Models for Life Sequences and Other Multivariate,
        Multichannel Categorical Time Series
Version: 1.0.6
Date: 2016-08-01
Author: Jouni Helske, Satu Helske
Maintainer: Jouni Helske <jouni.helske@jyu.fi>
Description: 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.
LazyData: true
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.2.0)
Imports: gridBase, igraph, Matrix, nloptr, numDeriv, Rcpp (>= 0.11.3),
        TraMineR (>= 1.8-8), graphics, grDevices, grid, methods, stats,
        utils
Suggests: MASS, nnet, knitr
License: GPL (>= 2)
Encoding: UTF-8
BugReports: https://github.com/helske/seqHMM/issues
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-08-01 12:56:50 UTC; jovetale
Repository: CRAN
Date/Publication: 2016-08-01 17:29:47
Built: R 3.3.2; x86_64-w64-mingw32; 2016-12-02 05:20:16 UTC; windows
Archs: i386, x64
