Nonparametric quantile estimation using importance sampling

DOI10.1007/s10463-016-0595-4zbMath1387.62052OpenAlexW2573710000MaRDI QIDQ1744716

Reinhard Tent, Adam Krzyżak, Michael Kohler, Harro Walk

Publication date: 19 April 2018

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-016-0595-4

zbMATH Keywords

rate of convergenceimportance samplingnonparametric quantile estimation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items

Nonparametric recursive quantile estimation, Estimation of extreme quantiles in a simulation model, Nonparametric quantile estimation using surrogate models and importance sampling

Cites Work

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• Nonparametric recursive quantile estimation
• Optimal global rates of convergence for noiseless regression estimation problems with adaptively chosen design
• Controlled stratification for quantile estimation
• Nonparametric orthogonal series estimators of regression: A class attaining the optimal convergence rate in \(L_ 2\)
• Fourier and Hermite series estimates of regression functions
• Distribution-free consistency results in nonparametric discrimination and regression function estimation
• Consistent nonparametric regression. Discussion
• A practical guide to splines
• An equivalence theorem for \(L_ 1\) convergence of the kernel regression estimate
• On the asymptotic normality of the \(L_2\)-error in partitioning regression estimation
• Inequalities for uniform deviations of averages from expectations with applications to nonparametric regression
• On the strong universal consistency of nearest neighbor regression function estimates
• Optimal global rates of convergence for nonparametric regression
• A distribution-free theory of nonparametric regression
• Quantile estimation with adaptive importance sampling
• Estimating Percentiles of Uncertain Computer Code Outputs
• Necessary and sufficient conditions for the pointwise convergence of nearest neighbor regression function estimates
• Nonparametric regression estimation using penalized least squares
• Approximate Bayesian inference for quantiles
• Nonparametric estimation via empirical risk minimization
• Computationally Efficient Nonparametric Importance Sampling
• Remarks on Non-Parametric Estimates for Density Functions and Regression Curves