mmppr: Markov Modulated Poisson Process for Unsupervised Event Detection in Time Series of Counts

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

Downloads:

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 El Capitan binaries: r-release: mmppr_0.1.tgz
OS X Mavericks binaries: r-oldrel: mmppr_0.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mmppr to link to this page.