Hidden Semi Markov Models for Multiple Observation Sequences: The<b>mhsmm</b>Package for<i>R</i>

Abstract

This paper describes the <strong>R</strong> package <strong>mhsmm</strong> 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.