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>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp (≥ 1.0.0), evd, extRemes, stats, MASS, mnormt, grDevices, graphics, utils |
| LinkingTo: | Rcpp |
| Published: | 2025-12-18 |
| DOI: | 10.32614/CRAN.package.HMMHSMM |
| Author: | Aimee Cody [aut], Ting Wang [cre, ctb] (Research Supervisor) |
| Maintainer: | Ting Wang <ting.wang at otago.ac.nz> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | HMMHSMM results |
| Reference manual: | HMMHSMM.html , HMMHSMM.pdf |
| Package source: | HMMHSMM_0.1.0.tar.gz |
| Windows binaries: | r-devel: HMMHSMM_0.1.0.zip, r-release: HMMHSMM_0.1.0.zip, r-oldrel: HMMHSMM_0.1.0.zip |
| macOS binaries: | r-release (arm64): HMMHSMM_0.1.0.tgz, r-oldrel (arm64): HMMHSMM_0.1.0.tgz, r-release (x86_64): HMMHSMM_0.1.0.tgz, r-oldrel (x86_64): HMMHSMM_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=HMMHSMM to link to this page.
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.