Fit Gaussian hidden Markov (or semi-Markov) models with / without autoregressive coefficients and with / without regularization. The fitting algorithm for the hidden Markov model is illustrated by Rabiner (1989) <doi:10.1109/5.18626>. The shrinkage estimation on the covariance matrices is based on the method by Ledoit et al. (2004) <doi:10.1016/S0047-259X(03)00096-4>. The shrinkage estimation on the autoregressive coefficients uses the elastic net shrinkage detailed in Zou et al. (2005) <doi:10.1111/j.1467-9868.2005.00503.x>.
| Version: | 1.0.5 |
| Depends: | R (≥ 3.0.0) |
| Imports: | Rcpp (≥ 0.12.9), glmnet |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2017-10-18 |
| Author: | Zekun (Jack) Xu, Ye Liu |
| Maintainer: | Zekun Xu <zekunxu at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | yes |
| CRAN checks: | rarhsmm results |
| Reference manual: | rarhsmm.pdf |
| Package source: | rarhsmm_1.0.5.tar.gz |
| Windows binaries: | r-devel: rarhsmm_1.0.5.zip, r-release: rarhsmm_1.0.5.zip, r-oldrel: rarhsmm_1.0.5.zip |
| OS X El Capitan binaries: | r-release: rarhsmm_1.0.5.tgz |
| OS X Mavericks binaries: | r-oldrel: rarhsmm_1.0.5.tgz |
| Old sources: | rarhsmm archive |
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