Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R

Jared O'Connell and Søren Højsgaard

Journal of Statistical Software, 2011, vol. 039, issue i04

Abstract: This paper describes the R package mhsmm which implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some unobserved (or hidden) state. Hidden Markov models only allow a geometrically distributed sojourn time in a given state, while hidden semi-Markov models extend this by allowing an arbitrary sojourn distribution. We demonstrate the software with simulation examples and an application involving the modelling of the ovarian cycle of dairy cows.

Date: 2011-03-09
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:039:i04

DOI: 10.18637/jss.v039.i04

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