|Authors:||Jared O'Connell, Søren Højsgaard|
|Title:||Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R|
|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.|
Page views:: 9978. Submitted: 2009-03-02. Published: 2011-03-09.
Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.