SPLITTING BEHAVIOR INTO BOUTS - A MAXIMUM-LIKELIHOOD APPROACH

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 likeli hood 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 t he two exponential processes and the proportion in which they are mixe d. The use of likelihood ratio tests in helping to determine whether t he data occur in bouts is also described and illustrated.