Controlled stratification for quantile estimation

Details Controlled stratification for quantile estimation Controlled stratification for quantile estimation

2008-02-18

arxiv.org/abs/0802.2426v2

Annals of Applied Statistics 2008, Vol. 2, No. 4, 1554-1580

Statistics

Methodology

Published in at http://dx.doi.org/10.1214/08-AOAS186 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Ins

Scientific paper

10.1214/08-AOAS186

In this paper we propose and discuss variance reduction techniques for the estimation of quantiles of the output of a complex model with random input parameters. These techniques are based on the use of a reduced model, such as a metamodel or a response surface. The reduced model can be used as a control variate; or a rejection method can be implemented to sample the realizations of the input parameters in prescribed relevant strata; or the reduced model can be used to determine a good biased distribution of the input parameters for the implementation of an importance sampling strategy. The different strategies are analyzed and the asymptotic variances are computed, which shows the benefit of an adaptive controlled stratification method. This method is finally applied to a real example (computation of the peak cladding temperature during a large-break loss of coolant accident in a nuclear reactor).

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