title: On the application of mixed hidden Markov models to multiple behavioural time series.
abstract: Analysing behavioural sequences and quantifying the likelihood of occurrences of different behaviours is a difficult task as motivational states are not observable. Furthermore, it is ecologically highly relevant and yet more complicated to scale an appropriate model for one individual up to the population level. In this manuscript (mixed) hidden Markov models (HMMs) are used to model the feeding behaviour of 54 subadult grey mouse lemurs (Microcebus murinus), small nocturnal primates endemic to Madagascar that forage solitarily. Our primary aim is to introduce ecologists and other users to various HMM methods, many of which have been developed only recently, and which in this form have not previously been synthesized in the ecological literature. Our specific application of mixed HMMs aims at gaining a better understanding of mouse lemur behaviour, in particular concerning sex-specific differences. The model we consider incorporates random effects for accommodating heterogeneity across animals, i.e. accounts for different personalities of the animals. Additional subject- and time-specific covariates in the model describe the influence of sex, body mass and time of night.
authors.affiliation: Courant Research Centre Evolution of Social Behaviour, University of Göttingen, Kellnerweg 6, 37077 Göttingen, Germany ; Behavioral Ecology and Sociobiology Unit, German Primate Center, Kellnerweg 4, 37077 Göttingen, Germany.
authors.forename: S
authors.initials: S
authors.lastname: Schliehe-Diecks
authors.forename: P M
authors.initials: PM
authors.lastname: Kappeler
authors.forename: R
authors.initials: R
authors.lastname: Langrock
keywords: behavioural analysis; maximum likelihood; motivational states; random effects; state-space model; subject-specific covariate
references.citation: Biometrics. 2008 Sep;64(3):807-815
references.pmid: 18047533
references.citation: Biol Rev Camb Philos Soc. 2007 May;82(2):291-318
references.pmid: 17437562
references.citation: Mol Ecol. 2005 Jul;14(8):2363-72
references.pmid: 15969720
references.citation: Proc Nutr Soc. 1999 Nov;58(4):765-72
references.pmid: 10817142
references.citation: Am J Phys Anthropol. 1998;Suppl 27:1-23
references.pmid: 9881521
references.citation: J Anim Ecol. 2006 Sep;75(5):1046-57
references.pmid: 16922840
references.citation: Theor Popul Biol. 1976 Apr;9(2):129-36
references.pmid: 1273796
references.citation: J Anim Ecol. 2009 Nov;78(6):1113-23
references.pmid: 19563470
references.citation: Am J Phys Anthropol. 2010 Feb;141(2):181-9
references.pmid: 19591211
references.citation: Ecology. 2009 Nov;90(11):3209-21
references.pmid: 19967876
references.citation: J Anim Ecol. 2011 Sep;80(5):1088-96
references.pmid: 21521216
references.citation: Horm Behav. 2000 Dec;38(4):250-61
references.pmid: 11104643
references.citation: Trends Ecol Evol. 2009 Dec;24(12):670-5
references.pmid: 19683827
references.citation: Oecologia. 2008 Sep;157(3):473-83
references.pmid: 18574599
references.citation: J Mol Biol. 1994 Feb 4;235(5):1501-31
references.pmid: 8107089
references.citation: Am J Primatol. 2001 Aug;54(4):181-92
references.pmid: 11468749
references.citation: Trends Ecol Evol. 2008 Feb;23(2):87-94
references.pmid: 18191283