Conditional properties of unconditional parametric bootstrap procedures for inference in exponential families
Higher-order inference about a scalar parameter in the presence of nuisance parameters can be achieved by bootstrapping, in circumstances where the parameter of interest is a component of the canonical parameter in a full exponential family. The optimal test, which is approximated, is a conditional one based on conditioning on the sufficient statistic for the nuisance parameter. A bootstrap procedure that ignores the conditioning is shown to have desirable conditional properties in providing third-order relative accuracy in approximation of p-values associated with the optimal test, in both continuous and discrete models. The bootstrap approach is equivalent to third-order analytical approaches, and is demonstrated in a number of examples to give very accurate approximations even for very small sample sizes. Copyright 2008, Oxford University Press.
Year of publication: |
2008
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Authors: | Diciccio, Thomas J. ; Young, G. Alastair |
Published in: |
Biometrika. - Biometrika Trust, ISSN 0006-3444. - Vol. 95.2008, 3, p. 747-758
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Publisher: |
Biometrika Trust |
Saved in:
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