Time-series of count data occur in many different contexts. A Markov-modulated Poisson process provides a framework for detecting anomalous events using an unsupervised learning approach.
| Version: | 0.1 |
| Depends: | R (≥ 3.0.2), expm, reshape2, stats, methods |
| Published: | 2016-01-11 |
| Author: | Graham Mueller [aut, cre] |
| Maintainer: | Peter Landwehr <peter.landwehr at giantoak.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | mmppr results |
| Reference manual: | mmppr.pdf |
| Package source: | mmppr_0.1.tar.gz |
| Windows binaries: | r-devel: mmppr_0.1.zip, r-release: mmppr_0.1.zip, r-oldrel: mmppr_0.1.zip |
| OS X binaries: | r-release: mmppr_0.1.tgz, r-oldrel: mmppr_0.1.tgz |
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