The University of Southampton
University of Southampton Institutional Repository

A mixed non-homogeneous hidden Markov model for categorical data, with application to alcohol consumption

Record type: Article

Hidden Markov models (HMMs) are frequently used to analyse longitudinal data, where the same set of subjects is repeatedly observed over time. In this context, several sources of heterogeneity may arise at individual and/or time level, which affect the hidden process, that is, the transition probabilities between the hidden states. In this paper, we propose the use of a finite mixture of non-homogeneous HMMs (NH-HMMs) to face the heterogeneity problem. The non-homogeneity of the model allows us to take into account observed sources of heterogeneity by means of a proper set of covariates, time and/or individual dependent, explaining the variations in the transition probabilities. Moreover, we handle the unobserved sources of heterogeneity at the individual level, due to, for example, omitted covariates, by introducing a random term with a discrete distribution. The resulting model is a finite mixture of NH-HMM that can be used to classify individuals according to their dynamic behaviour or to estimate a mixed NH-HMM without any assumption regarding the distribution of the random term following the non-parametric maximum likelihood approach. We test the effectiveness of the proposal through a simulation study and an application to real data on alcohol abuse.

Full text not available from this repository.


Maruotti, Antonello and Rocci, Roberto (2012) A mixed non-homogeneous hidden Markov model for categorical data, with application to alcohol consumption Statistics in Medicine, 31, (9), pp. 871-886. (doi:10.1002/sim.4478). (PMID:22302505).

More information

e-pub ahead of print date: 3 February 2012
Published date: 30 April 2012
Keywords: mixed hidden markov models, random effects models, penalized npml, longitudinal data
Organisations: Statistics, Statistical Sciences Research Institute


Local EPrints ID: 340813
ISSN: 0277-6715
PURE UUID: 43121c42-49b4-4341-99f8-3b598a88c074

Catalogue record

Date deposited: 04 Jul 2012 09:23
Last modified: 18 Jul 2017 05:41

Export record



Author: Antonello Maruotti
Author: Roberto Rocci

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.