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IMPROVING THE NORMALIZED IMPORTANCE SAMPLING ESTIMATOR

Published online by Cambridge University Press:  30 July 2012

Samim Ghamami
Affiliation:
Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA 90089 E-mails: [email protected]; [email protected]
Sheldon M. Ross
Affiliation:
Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA 90089 E-mails: [email protected]; [email protected]

Abstract

The normalized importance sampling estimator allows the target density f to be known only up to a multiplicative constant. We indicate how it can be derived by a delta method-based approximation of a Rao–Blackwellized acceptance rejection estimator. Using additional terms in the delta method then results on a new estimator that also only requires f to be known only up to a multiplicative constant. Numerical examples indicate that the new estimator usually outperforms the normalized importance sampling estimator in terms of mean square error.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2012

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