作者：Chopin, Nicolas; Crucinio, Francesca R.; Singh, Sumeetpal S.
作者单位：Institut Polytechnique de Paris; ENSAE Paris; University of Turin; University of Wollongong
摘要：Given a smooth function $ f $, we develop a general approach to turn Monte Carlo samples with expectation $ m $ into an unbiased estimate of $ f(m) $. Specifically, we develop estimators that are based on randomly truncating the Taylor series expansion of $ f $ and estimating the coefficients of the truncated series. We derive their properties and propose a strategy to set their tuning parameters (which depend on $ m $) automatically, with a view to making the whole approach simple to use. We ...
