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B1912
Title: A new selection criterion for statistical home range estimation Authors:  Amparo Baillo - Universidad Autonoma de Madrid (Spain) [presenting]
Jose E Chacon - Universidad de Extremadura (Spain)
Abstract: The home range of a specific animal describes the geographic surface where this individual spends most of the time while carrying out its usual activities (eating, resting, reproduction, ...). Although a well-established definition of this concept is lacking, there are a variety of home range estimators. We address the open question of choosing the ``best'' home range from a collection of them based on the same sample of locations. We introduce the penalized overestimation ratio, a numerical index to rank the estimated home ranges. The key idea is to balance the excess area covered by the estimator (with respect to the original sample) and a shape descriptor measuring the over-adjustment of the home range to the data. To our knowledge, apart from computing the home range area, our ranking procedure is the first one which is both applicable to real data and to any type of home range estimator. Furthermore, the analysis and optimization of the selection index provides a way to select the tuning parameters of the home range estimators. For illustration purposes, using R, firstly we apply the new procedure to a set of real locations of a Mongolian wolf. Secondly, we carry out a Monte Carlo study to compare the true home range with the estimated one selected by our selection proposal.