Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R
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| Authors | J. Michael O'connell, Søren Højsgaard |
| Journal/Conference Name | Journal of Statistical Software |
| Paper Category | Other |
| Paper 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 of publication | 2011 |
| Code Programming Language | R |
| Comment |
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