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Zapiski Nauchnykh Seminarov POMI, 2014, Volume 431, Pages 82–96
(Mi znsl6096)
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This article is cited in 1 scientific paper (total in 1 paper)
Asymptotically efficient importance sampling for the bootstrap
M. S. Ermakovab a St. Petersburg State University, St. Petersburg, Russia
b Institute of Problems of Mechanical Engineering, Russian Academy of Sciences, St. Petersburg, Russia
Abstract:
We establish Large Deviation Principle for conditional moderate deviation probabilities of weighted bootstrap empirical measures given empirical measures. On the base of this result, for the problem of estimation of moderate deviation probabilities of statistics having Hadamard derivatives, we prove asymptotic efficiency of importance sampling based on influence functions.
Key words and phrases:
importance sampling, large deviation principle, moderate deviations, bootstrap, empirical measure.
Received: 10.11.2014
Citation:
M. S. Ermakov, “Asymptotically efficient importance sampling for the bootstrap”, Probability and statistics. Part 21, Zap. Nauchn. Sem. POMI, 431, POMI, St. Petersburg, 2014, 82–96; J. Math. Sci. (N. Y.), 214:4 (2016), 474–483
Linking options:
https://www.mathnet.ru/eng/znsl6096 https://www.mathnet.ru/eng/znsl/v431/p82
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Abstract page: | 161 | Full-text PDF : | 40 | References: | 45 |
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