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Modelling larval movement data from individual bioassays
Authors:Chris R. McLellan  Bruce J. Worton  William Deasy  A. Nicholas E. Birch
Affiliation:1. School of Mathematics and Maxwell Institute for Mathematical Sciences, The University of Edinburgh, James Clerk Maxwell Building, King's Buildings, Edinburgh, EH9 3JZ, UK;2. SRUC, West Mains Road, Edinburgh, EH9 3JG, UK;3. The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK
Abstract: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.
Keywords:Diffusion  Hidden Markov models  Mixtures  Model comparison
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