Asymptotically Efficient Importance Sampling for Bootstrap
- Авторлар: Ermakov M.S.1
-
Мекемелер:
- Institute of Mechanical Engineering Problems RAS
- Шығарылым: Том 214, № 4 (2016)
- Беттер: 474-483
- Бөлім: Article
- URL: https://ogarev-online.ru/1072-3374/article/view/237433
- DOI: https://doi.org/10.1007/s10958-016-2791-4
- ID: 237433
Дәйексөз келтіру
Аннотация
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.
Негізгі сөздер
Авторлар туралы
M. Ermakov
Institute of Mechanical Engineering Problems RAS
Хат алмасуға жауапты Автор.
Email: erm2512@mail.ru
Ресей, St.Petersburg
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