학술논문
Asymptotically Efficient Importance Sampling for Bootstrap.
Document Type
Article
Author
Source
Subject
*ASYMPTOTIC distribution
*STATISTICAL sampling
*STATISTICAL bootstrapping
*LARGE deviations (Mathematics)
*MATHEMATICAL proofs
*
*
*
*
Language
ISSN
1072-3374
Abstract
The Large Deviation Principle is proved for the conditional probabilities of moderate deviations of weighted empirical bootstrap measures with respect to a fixed empirical measure. Using this LDP for the problem of calculation of moderate deviation probabilities of differentiable statistical functionals, it is shown that the importance sampling based on influence function is asymptotically efficient. [ABSTRACT FROM AUTHOR]