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Activity Number: 29
Type: Contributed
Date/Time: Sunday, August 6, 2006 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #306952
Title: Conditional Properties of a Parametric Bootstrap
Author(s): Russell Zaretzki*+
Companies: University of Tennessee
Address: 328 Stokely Management Center, Knoxville, TN, 37996-0532,
Keywords: bootstrap ; asymptotics ; conditional inference ; likelihood theory
Abstract:

DiCiccio, Martin and Stern(2O01) introduced the parametric bootstrap of the signed root statistic as a useful computational alternative to analytic approximations when highly accurate statistical inference is desired. This performance is equivalent to asymptotic techniques such as the r-star formula; see Barndorff-Nielson(1986). In addition, simulation examples contained in DiCiccio (2001) suggest that this bootstrap technique can produce extremely accurate conditional inferences. The present work further investigates these conditional properties. In particular, we prove that, in the presence of nuisance parameters, inferences based on a parametric bootstrap of the signed root are conditionally accurate to order 1/n. This project is joint work with Tom DiCiccio and G.A. Young.

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