Blanchet, J. H., Glynn, P. W., & Pei, Y. (2019). Unbiased Multilevel Monte Carlo: Stochastic Optimization, Steady-state Simulation, Quantiles, and Other Applications. ArXiv. /abs/1904.09929

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Abstract

We present general principles for the design and analysis of unbiased Monte Carlo estimators in a wide range of settings. Our estimators posses finite work-normalized variance under mild regularity conditions. We apply our estimators to various settings of interest, including unbiased optimization in Sample Average Approximations, unbiased steady-state simulation of regenerative processes, quantile estimation and nested simulation problems.

Authors
Jose H Blanchet, Peter W Glynn, Yanan Pei
Publication date
2019/4/22
Journal
arXiv preprint arXiv:1904.09929