HMMCont: Hidden Markov Model for Continuous Observations Processes

The package includes the functions designed to analyse continuous observations processes with the Hidden Markov Model approach. They include Baum-Welch and Viterbi algorithms and additional visualisation functions. The observations are assumed to have Gaussian distribution and to be weakly stationary processes. The package was created for analyses of financial time series, but can also be applied to any continuous observations processes.

Version: 1.0
Published: 2014-02-11
Author: Mikhail A. Beketov
Maintainer: Mikhail A. Beketov <mikhail.beketov at gmx.de>
License: GPL-3
NeedsCompilation: no
CRAN checks: HMMCont results

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Reference manual: HMMCont.pdf
Package source: HMMCont_1.0.tar.gz
Windows binaries: r-devel: HMMCont_1.0.zip, r-release: HMMCont_1.0.zip, r-oldrel: HMMCont_1.0.zip
OS X El Capitan binaries: r-release: HMMCont_1.0.tgz
OS X Mavericks binaries: r-oldrel: HMMCont_1.0.tgz

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