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Splitting Behaviour Into Bouts; a Maximum Likelihood Approach

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One method of splitting behaviour into bouts is to model the data as a mixture of two (or more) exponential distributions and to calculate a bout criterion from the resulting parameter estimates. The parameter estimates under a mixture model can be obtained using a maximum likelihood approach. The sample size required to obtain reasonable estimates of the parameters using this approach is investigated using simulated data, and found to depend on the ratio between the two densities of the two exponential processes and the proportion in which they are mixed. The use of likelihood ratio tests in helping to determine whether the data occur in bouts is also described and illustrated.

Affiliations: 1: Central Science Laboratory, Tangley Place, Worplesdon, Surrey, GU3 3LQ, U.K.; 2: Department of Applied Statistics, University of Reading, Reading, RG6 2FN, U.K.; 3: Department of Pure and Applied Zoology, University of Reading, Reading, RG6 2AJ, U.K.


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