Abstract. In this paper kernel methods for the non parametric estimation of the utiiz~tion distribution from a random sample oflocational observations made on an animal m Its ho~e range are described. They are of flexible form, thus can be used where simple p~ramet~c models are found to be inappropriate or difficult to specifY. Two examples are given to Illustrate ~he fixed ~nd adaptive kernel ~pproaches in data analysis and to compare t~e method~. Vanous chmces for the smoothmg parameter used in kernel methods are discussed. Smce kernel methods give alternative approaches to the Anderson (1982) Fourier transform method, some comparisons are made.

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