Finite Mixture of Hidden Markov Model

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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install.packages("MHMM")

1.0.0 by Matthieu Marbac, 4 months ago


Browse source code at https://github.com/cran/MHMM


Authors: Marie Du-Roy-De-Chaumary , Matthieu Marbac and Fabien Navarro


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, methods, parallel, ggplot2, reshape2, gridExtra

Linking to Rcpp, RcppArmadillo, BH


See at CRAN