Title: Oracle Importance Sampling for Stochastic Simulation Models,
Abstract: We consider the problem of estimating an expected outcome from a stochastic
simulation model using importance sampling. We propose a two-stage procedure
that involves a regression stage and a sampling stage to construct our
estimator. We introduce a parametric and a nonparametric regression estimator
in the first stage and study how the allocation between the two stages affects
the performance of final estimator. We derive the oracle property for both
approaches. We analyze the empirical performances of our approaches using two
simulated data and a case study on wind turbine reliability evaluation.