Controlled stratification for quantile estimation

DOI10.1214/08-AOAS186zbMath1156.62023arXiv0802.2426MaRDI QIDQ999679

Josselin Garnier, Claire Cannamela, Bertrand Iooss

Publication date: 10 February 2009

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0802.2426

zbMATH Keywords

Monte Carlo methodsvariance reductionquantile estimationcomputer experimentsnuclear safety

Mathematics Subject Classification ID

Related Items (14)

Bounding rare event probabilities in computer experiments ⋮ Bregman superquantiles. Estimation methods and applications ⋮ Nonparametric recursive quantile estimation ⋮ Accelerated Monte Carlo estimation of exceedance probabilities under monotonicity constraints ⋮ Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models ⋮ Risk bounds when learning infinitely many response functions by ordinary linear regression ⋮ A Tutorial on Quantile Estimation via Monte Carlo ⋮ Conditional-Value-at-Risk Estimation via Reduced-Order Models ⋮ Bayesian Subset Simulation ⋮ Uncertainty quantification of stochastic simulation for black-box computer experiments ⋮ Nonparametric quantile estimation using importance sampling ⋮ Adaptive optimal allocation in stratified sampling methods ⋮ Nonparametric quantile estimation using surrogate models and importance sampling ⋮ Nonparametric importance sampling for wind turbine reliability analysis with stochastic computer models

Uses Software

• EGO
• ElemStatLearn

Cites Work

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