A numerical investigation of the accuracy of parametric bootstrap for discrete data

Standard first order tests have size error that decreases as m−1/2 where m is a measure of sample size. Parametric bootstrap tests use an exact calculation of the P-value, assuming nuisance parameters equal their null maximum likelihood estimates. It is commonly believed that their performance is driven by asymptotics, notwithstanding some confusion in the literature on asymptotic error rates.

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Year of publication:	2013
Authors:	Lloyd, Chris J.
Published in:	Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 61.2013, C, p. 1-6
Publisher:	Elsevier
Subject:	Bootstrap \| Exact test \| Nuisance parameters \| Tests of non-inferiority

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011056497