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Title: Adaptive Monte Carlo Variance Reduction with Two-time-scale Stochastic Approximation
Authors: Kawai, Reiichiro
First Published: Aug-2007
Publisher: Brill Academic Publishers
Citation: Monte Carlo Methods and Applications, 2007, 13 (3), pp. 197–217.
Abstract: Combined control variates and importance sampling variance reduction and its two-fold optimality are investigated. Two-time-scale stochastic approximation algorithm is applied in parameter search for the combination and almost sure convergence of the algorithm to the unique optimum is proved. The parameter search procedure is further incorporated into adaptive Monte Carlo simulation, and its law of large numbers and central limit theorem are proved to hold. An numerical example is provided to illustrate the effectiveness of the method.
DOI Link: 10.1515/mcma.2007.010
ISSN: 0929-9629
Type: Article
Rights: This is the author's final draft of the paper published as Monte Carlo Methods and Applications, 2007, 13 (3), pp. 197-217. The final version is available from Doi: 10.1515/mcma.2007.010
Appears in Collections:Published Articles, Dept. of Mathematics

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