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Weak Error for Nested Multilevel Monte Carlo
Methodology and Computing in Applied Probability ( IF 1.0 ) Pub Date : 2020-01-28 , DOI: 10.1007/s11009-019-09751-3
Daphné Giorgi , Vincent Lemaire , Gilles Pagès

This article discusses MLMC estimators with and without weights, applied to nested expectations of the form Ef(EF(Y,Z)|Y ). More precisely, we are interested on the assumptions needed to comply with the MLMC framework, depending on whether the payoff function f is smooth or not. A new result to our knowledge is given when f is not smooth in the development of the weak error at an order higher than 1, which is needed for a successful use of MLMC estimators with weights.

中文翻译:

嵌套多层蒙特卡洛的微弱误差

本文讨论了带权重和不带权重的MLMC估计器,这些估计器适用于E fE FYZ)| Y)形式的嵌套期望。更准确地说,我们对符合MLMC框架所需的假设感兴趣,这取决于收益函数f是否平滑。当f在弱误差的发展中不平稳且阶次高于1时,将给出我们所知的新结果,这是成功使用带权重的MLMC估计量所必需的。
更新日期:2020-01-28
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