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Fits hidden Markov models with discrete non-parametric observation distributions to data sets. The observations may be univariate or bivariate. Simulates data from such models. Finds most probable underlying hidden states, the most probable sequences of such states, and the log likelihood of a collection of observations given the parameters of the model. Auxiliary predictors are accommodated in the univariate setting.
| Version: | 3.0-9 |
| Depends: | R (≥ 2.10) |
| Imports: | nnet (≥ 7.3.12) |
| Published: | 2022-09-26 |
| Author: | Rolf Turner |
| Maintainer: | Rolf Turner <r.turner at auckland.ac.nz> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Materials: | ChangeLog |
| CRAN checks: | hmm.discnp results |
| Reference manual: | hmm.discnp.pdf |
| Package source: | hmm.discnp_3.0-9.tar.gz |
| Windows binaries: | r-devel: hmm.discnp_3.0-9.zip, r-release: hmm.discnp_3.0-9.zip, r-oldrel: hmm.discnp_3.0-9.zip |
| macOS binaries: | r-release (arm64): hmm.discnp_3.0-9.tgz, r-oldrel (arm64): hmm.discnp_3.0-9.tgz, r-release (x86_64): hmm.discnp_3.0-9.tgz, r-oldrel (x86_64): hmm.discnp_3.0-9.tgz |
| Old sources: | hmm.discnp archive |
| Reverse suggests: | dbd |
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