Package: HMMHSMM
Type: Package
Title: Inference and Estimation of Hidden Markov Models and Hidden
        Semi-Markov Models
Version: 0.1.0
Authors@R: c(person("Aimee", "Cody", email = "codai942@student.otago.ac.nz", role = c("aut")), person("Ting", "Wang",email = "ting.wang@otago.ac.nz", role = c("cre", "ctb"), comment = "Research Supervisor"))
Maintainer: Ting Wang <ting.wang@otago.ac.nz>
Description: Provides flexible maximum likelihood estimation and inference for Hidden
    Markov Models (HMMs) and Hidden Semi-Markov Models (HSMMs), as well as the
    underlying systems in which they operate. The package supports a wide range
    of observation and dwell-time distributions, offering a flexible modelling
    framework suitable for diverse practical data. Efficient implementations of 
    the forward-backward and Viterbi algorithms are provided via 'Rcpp' for enhanced 
    computational performance. Additional functionality includes model simulation, 
    residual analysis, non-initialised estimation, local and global decoding, 
    calculation of diverse information criteria, computation of confidence intervals 
    using parametric bootstrap methods, numerical covariance matrix estimation, and 
    comprehensive visualisation functions for interpreting the data-generating 
    processes inferred from the models. Methods follow standard approaches described 
    by Guédon (2003) <doi:10.1198/1061860032030>, 
    Zucchini and MacDonald (2009, ISBN:9781584885733), and 
    O'Connell and Højsgaard (2011) <doi:10.18637/jss.v039.i04>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.0), evd, extRemes, stats, MASS, mnormt,
        grDevices, graphics, utils
LinkingTo: Rcpp
Depends: R (>= 3.5.0)
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2025-12-12 19:13:26 UTC; aimee
Author: Aimee Cody [aut],
  Ting Wang [cre, ctb] (Research Supervisor)
Repository: CRAN
Date/Publication: 2025-12-18 14:20:10 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 00:55:38 UTC; unix
Archs: HMMHSMM.so.dSYM
