title: Robust estimates of wildlife location using telemetry data.
abstract: The location of wildlife is frequently determined using telemetry data gathered at short intervals. If radio transmissions are reflected, as often occurs in mountainous regions, then existing location estimation techniques re unreliable. We explore the effects of gross observation errors upon current analyses and suggest an alternative analysis based on robust state-space time-series modeling. We determine location estimates and their precisions, both for simulated and real mule-deer data, using current and robust procedures. Implementation and specification of filter parameters are also discussed. We conclude that the proposed filter-smoother is similar to the Gaussian filter-smoother when data are not greatly contaminated and that the robust version improves upon location estimates when contamination is large.
authors.affiliation: Department of Statistics, University of Wyoming, Laramie 82071-3332.
authors.forename: R
authors.initials: R
authors.lastname: Anderson-Sprecher
mesh_terms: D000823:Animal Identification Systems; D000818:Animals; D000835:Animals, Wild; D001522:Behavior, Animal; D003670:Deer; D008962:Models, Theoretical; D013223:Statistics as Topic; D013686:Telemetry / Q000379:methods*