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Moving particles: A parallel optimal Multilevel Splitting method with application in quantiles estimation and meta-model based algorithms

机译:移动粒子:一种并行的最优多级分裂方法,在分位数估计和基于元模型的算法中的应用

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摘要

Considering the issue of estimating small probabilities p, i.e. measuring a rare domain F = {x vertical bar g(x) > q} with respect to the distribution of a random vector X, Multilevel Splitting strategies (also called Subset Simulation) aim at writing F as an intersection of less rare events (nested subsets) such that their measures are conditionally easily computable. However the definition of an appropriate sequence of nested subsets remains an open issue.
机译:考虑到估计小概率p的问题,即相对于随机矢量X的分布测量稀有域F = {x竖线g(x)> q},多级拆分策略(也称为子集仿真)旨在编写F是少见事件(嵌套子集)的交集,因此可以有条件地轻松计算其度量。但是,嵌套子集的适当序列的定义仍然是一个未解决的问题。

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