JSM 2004 Online Program

Abstract #300274

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Activity Number:	362
Type:	Invited
Date/Time:	Wednesday, August 11, 2004 : 2:00 PM to 3:50 PM
Sponsor:	Section on Statistics and the Environment
Abstract - #300274
Title:	Bootstrapping-dependent Data: Difficulties and Potential Solutions
Author(s):	Mark L. Taper*+
Companies:	Montana State University
Address:	Dept. of Ecology, Bozeman, MT, 59717,
Keywords:	bootstrapping ; dependent data ; parametric bootstrap ; estimating equations
Abstract:	Bootstraping is an increasingly important statistical tool, allowing statistical inferences to be made in situations where analytic solutions are difficult. However, bootstrapping is not a panacea. A fundamental assumption of bootstraping is that the resampled entities are independent. In many ecological problems, such as time-series, spatial data, and genetic data independent entities are dificult to find. I discuss strategies for constructing useful bootstrap inference in such cases using parametric bootstrapping, conditioning to achieve independence, bootstraping of evidence functions, and bootstraping of random effects.

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