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#Dong nakayama quantile latin hypercube sampling series
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Bahadur, A note on quantiles in large samples, Ann. Wilson, Correlation-induction techniques for estimating quantiles in simulation experiments, Oper. We first prove the convergence of QMC-based quantile estimates under very mild conditions, and then establish a deterministic error bound of $O(N^)$ for arbitrarily small $\epsilon >0$.
This paper focuses on the use of the quasi-Monte Carlo (QMC) method, whose convergence rate is asymptotically better than Monte Carlo in the numerical integration. Convergence analysis of quasi-Monte Carlo sampling for quantile and expected shortfallĪbstract: Quantiles and expected shortfalls are usually used to measure risks of stochastic systems, which are often estimated by Monte Carlo methods.
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