Bootstrapping weighted empirical processes that do not converge weakly

We show that the bootstrap method provides valid approximations to the sampling distribution of a weighted empirical process on D[0,1] even in the cases where it fails to converge weakly. Furthermore, the result is applied to construct valid bootstrap confidence sets in such pathological cases.

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Year of publication:	1998
Authors:	Lahiri, Soumendra Nath
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 37.1998, 3, p. 295-302
Publisher:	Elsevier
Keywords:	Weighted empirical process Bootstrap Weak convergence Confidence sets

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

Persistent link: https://www.econbiz.de/10005254758