Clustering of high dimensional data with Hidden Markov Model on Variable Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin Lin and Jia Li (2017) <http://jmlr.org/papers/v18/16-342.html>.
| Version: | 1.0 |
| Depends: | methods |
| Imports: | Rcpp (≥ 0.12.16), RcppProgress (≥ 0.1) |
| LinkingTo: | Rcpp, RcppProgress |
| Suggests: | knitr, rmarkdown |
| Published: | 2018-07-29 |
| Author: | Yevhen Tupikov [aut, cre], Lin Lin [aut], Jia Li [aut] |
| Maintainer: | Yevhen Tupikov <yzt116 at psu.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| CRAN checks: | HDclust results |
| Reference manual: | HDclust.pdf |
| Vignettes: |
A quick tour of HDclust |
| Package source: | HDclust_1.0.tar.gz |
| Windows binaries: | r-devel: HDclust_1.0.zip, r-release: HDclust_1.0.zip, r-oldrel: HDclust_1.0.zip |
| OS X binaries: | r-release: HDclust_1.0.tgz, r-oldrel: HDclust_1.0.tgz |
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