Abstract
Various models, both statistical and non-statistical, which have been proposed for analysing data sets collected in home range studies, are described and compared. These models may be suitable for analysing locational data obtained by such sampling methods as radio tracking or live trapping. The most useful methods for analysing home range data sets involve describing an animal's range by a probability density function of location, called the utilization distribution. Robust methods of estimation of the utilization distribution are related to the estimation of the probability function, Of this type of approach, the method of Ford and Krumme is criticised. The Harmonic Mean method of Dixon and Chapman is shown to be an improper form of the statistical method of kernel estimation. A comparison of the properties of all the models for home range considered here shows that both the Fourier Transform method proposed by D.J. Anderson and the kernel method are good because of their flexibility. The assumption of independence of locational observations which is often made is discussed and shown to be important, especially for data collected by radio tracking. Some limitations of home range studies are considered.
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