Bootstrapping modified goodness-of-fit statistics with estimated parameters

Goodness-of-fit tests are proposed for testing a composite null hypothesis that is a general parametric family of distribution functions. They are distribution-free under the null hypothesis and have a limiting normal distribution under the null and the alternative hypothesis. To avoid the estimation of the asymptotic variance under the alternative hypothesis, we propose consistent bootstrap estimators.

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Year of publication:	2005
Authors:	Janssen, Paul ; Swanepoel, Jan ; Veraverbeke, Noël
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 71.2005, 2, p. 111-121
Publisher:	Elsevier
Keywords:	Bootstrap Consistency Estimated parameters Goodness-of-fit U-statistics

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

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005224120