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MHMM (version 1.0.0)

Finite Mixture of Hidden Markov Model

Description

Estimation of the latent states and partition by maximum likelihood. Model can be used for analyzing accelerometer data. In such a case, the latent states corresponds to activity levels and the partition permits to consider heterogeneity within the population. Emission laws are zero-inflated gamma distributions. Their parameters depends on the latent states but not on the partition, to compare the time spent by activity levels between classes. Model description is available in Du Roy de Chaumaray, M. and Marbac, M. and Navarro, F. (2019) .

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Version

Install

install.packages('MHMM')

Monthly Downloads

8

Version

1.0.0

License

GPL (>= 2)

Maintainer

Matthieu Marbac

Last Published

March 20th, 2020

Functions in MHMM (1.0.0)

accelero

Accelerometer data
mhmmdata-class

Constructor of '>mhmmdata class
MHMM-package

Finite Mixture of Hidden Markov Models for accelerometer data
plot

rdata.mhmm

Generator
mhmm

Mixture model of Hidden Markov Models.
mhmmparam-class

Constructor of '>mhmmparam class
mhmmresults-class

Constructor of '>mhmmresults class