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

Chris J. Lloyd

Computational Statistics & Data Analysis, 2013, vol. 61, issue C, 1-6

Abstract: 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.

Keywords: Bootstrap; Exact test; Nuisance parameters; Tests of non-inferiority (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:61:y:2013:i:c:p:1-6

DOI: 10.1016/j.csda.2012.09.015

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