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Bootstrapping weighted empirical processes that do not converge weakly

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  • Lahiri, Soumendra Nath

Abstract

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.

Suggested Citation

  • Lahiri, Soumendra Nath, 1998. "Bootstrapping weighted empirical processes that do not converge weakly," Statistics & Probability Letters, Elsevier, vol. 37(3), pages 295-302, March.
    • Handle: RePEc:eee:stapro:v:37:y:1998:i:3:p:295-302
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    References listed on IDEAS

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    1. Galen R. Shorack, 1979. "The weighted empirical process of row independent random variables with arbitrary distribution functions," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 33(4), pages 169-189, December.
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