HMMCont: Hidden Markov Model for Continuous Observations Processes

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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.

Author
Mikhail A. Beketov
Date of publication
2014-02-11 17:15:51
Maintainer
Mikhail A. Beketov <mikhail.beketov@gmx.de>
License
GPL-3
Version
1.0

View on CRAN

Man pages

baumwelchcont
Baum-Welch Algorithm
HMMCont-package
Hidden Markov Model for Continuous Observations Processes
hmmcontSimul
Simulation of an observation and underlying Markov processes...
hmmsetcont
Setting an initial HMM object
logreturns
Calculating Log-returns
Prices
A dummy data set of prices.
statesDistributionsPlot
Probability Density Functions of the States
viterbicont
Viterbi Algorithm

Files in this package

HMMCont
HMMCont/NAMESPACE
HMMCont/data
HMMCont/data/Prices.rda
HMMCont/R
HMMCont/R/statesDistributionsPlot.R
HMMCont/R/summary.ContObservHMM.R
HMMCont/R/print.ContObservHMM.R
HMMCont/R/viterbicont.R
HMMCont/R/hmmcontSimul.R
HMMCont/R/hmmsetcont.R
HMMCont/R/baumwelchcont.R
HMMCont/R/logreturns.R
HMMCont/R/plot.ContObservHMM.R
HMMCont/MD5
HMMCont/DESCRIPTION
HMMCont/man
HMMCont/man/viterbicont.Rd
HMMCont/man/hmmsetcont.Rd
HMMCont/man/hmmcontSimul.Rd
HMMCont/man/statesDistributionsPlot.Rd
HMMCont/man/Prices.Rd
HMMCont/man/baumwelchcont.Rd
HMMCont/man/HMMCont-package.Rd
HMMCont/man/logreturns.Rd