Sequence Analysis and Transition Models

Détails

ID Serval
serval:BIB_EE6BCEBF29D4
Type
Partie de livre
Sous-type
Chapitre: chapitre ou section
Collection
Publications
Titre
Sequence Analysis and Transition Models
Titre du livre
Encyclopedia of Animal Behavior
Auteur(s)
Berchtold André
Editeur
Elsevier, Academic Press
ISBN
9780128132517
Statut éditorial
Publié
Date de publication
2019
Peer-reviewed
Oui
Editeur scientifique
Choe Jae Chun
Volume
3
Pages
506-517
Edition
2nd ed.
Langue
anglais
Résumé
The behavior of an animal, with or without interaction with its environment, can generally be decomposed into a set of
mutually excluding activity categories such as play, exploration, or rest. Thus, the data consist of one or several series of
successive activities which can be used to answer the following questions: Does the probability of observing a particular
activity depend on the preceding observed activities? Do some particular patterns of successive activities appear more often than expected by chance only? Which external events influence the behavior of this animal?
This article covers several related methods used to answer these questions. At the base is the need to compute and analyze a transition probability, the probability of observing a particular activity in relation to the past. A Markov chain is a stochastic answer to this kind of problem, when lag-sequential analysis refers to a less formalized approach aimed at the identification of the most usual patterns of activities. We review here the basic principles of these two approaches and detail some advances such as the formulation of sequence analysis as log-linear models, the use of mixtures to obtain parsimonious models, the concept of hidden Markov models incorporating latent information, and the use of these models for clustering purpose.
Mots-clé
Bayesian information criterion (BIC), Clustering, Double chain markov model (DCMM), Hidden markov model (HMM), Lag-sequential analysis, Log-linear model, Markov chain, Mixture transition distribution (MTD) model, Stable distribution, Time dependence, Transition matrix
Création de la notice
30/01/2019 20:58
Dernière modification de la notice
21/08/2019 5:11
Données d'usage