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Modelling larval movement data from individual bioassays
Author(s) -
McLellan Chris R.,
Worton Bruce J.,
Deasy William,
Birch A. Nicholas E.
Publication year - 2015
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201400035
Subject(s) - bioassay , larva , inference , hidden markov model , movement (music) , markov model , biological system , experimental data , computer science , markov chain , ecology , biology , statistics , artificial intelligence , mathematics , machine learning , philosophy , aesthetics
We consider modelling the movements of larvae using individual bioassays in which data are collected at a high‐frequency rate of five observations per second. The aim is to characterize the behaviour of the larvae when exposed to attractant and repellent compounds. Mixtures of diffusion processes, as well as Hidden Markov models, are proposed as models of larval movement. These models account for directed and localized movements, and successfully distinguish between the behaviour of larvae exposed to attractant and repellent compounds. A simulation study illustrates the advantage of using a Hidden Markov model rather than a simpler mixture model. Practical aspects of model estimation and inference are considered on extensive data collected in a study of novel approaches for the management of cabbage root fly.