Article
Licensed
Unlicensed
Requires Authentication
Importance sampling for simulations of moderate deviation probabilities of statistics
-
Mikhail Ermakov
Published/Copyright:
September 25, 2009
Summary
In recent years importance has become the standard tool for estimation of probabilities of rare events. Of special interest is efficient importance sampling which allows a substantial reduction of the computational burden. Efficiency of importance sampling has been proved (see Sadowsky and Bucklew [19]) under rather strong assumptions, which often cannot be verified for particular test statistics and estimators. In this paper we show that efficient importance sampling correctly works for calculation of moderate deviation probabilities of statistics having influence functions.
:
Received: 2006-April-23
Accepted: 2008-January-16
Published Online: 2009-09-25
Published in Print: 2007-10
© Oldenbourg Wissenschaftsverlag
You are currently not able to access this content.
You are currently not able to access this content.
Articles in the same Issue
- Letter from the editor
- Importance sampling for simulations of moderate deviation probabilities of statistics
- Dynamic utility-based good deal bounds
- Pricing and hedging with globally and instantaneously vanishing risk
- Bootstrapping L2-type statistics in copula density testing
Keywords for this article
importance sampling;
moderate deviations;
influence functions;
M-statistics
Articles in the same Issue
- Letter from the editor
- Importance sampling for simulations of moderate deviation probabilities of statistics
- Dynamic utility-based good deal bounds
- Pricing and hedging with globally and instantaneously vanishing risk
- Bootstrapping L2-type statistics in copula density testing
