Quantile estimation with adaptive importance sampling

DOI10.1214/09-AOS745zbMath1183.62141arXiv1002.4946MaRDI QIDQ2380103

Markus Leippold, Daniel Egloff

Publication date: 24 March 2010

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

Full work available at URL: https://arxiv.org/abs/1002.4946

zbMATH Keywords

stochastic approximationlaw of iterated logarithmquantile estimationadaptive importance samplingRobbins-Monro

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05) Monte Carlo methods (65C05) Strong limit theorems (60F15) Stochastic approximation (62L20)

Related Items (10)

Nonparametric recursive quantile estimation ⋮ Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis ⋮ Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models ⋮ Nonparametric quantile estimation using importance sampling ⋮ Estimation of extreme quantiles in a simulation model ⋮ Fast simulations in credit risk ⋮ Convergence of Markovian Stochastic Approximation with Discontinuous Dynamics ⋮ Risk-Averse Approximate Dynamic Programming with Quantile-Based Risk Measures ⋮ Nonparametric quantile estimation using surrogate models and importance sampling ⋮ Rare Event Estimation for Computer Models

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