Estimation of the quantile function using Bernstein–Durrmeyer polynomials

DOI10.1080/10485252.2013.826355zbMath1359.62109OpenAlexW2043661225MaRDI QIDQ5419452

Andrey Pepelyshev, Ewaryst Rafajłowicz, Ansgar Steland

Publication date: 6 June 2014

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2013.826355

zbMATH Keywords

order statisticsconvergence rateadaptationnonparametric estimationsampling planfinancial and actuarial risk

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (2)

On the properties of Hermite series based distribution function estimators ⋮ Nonparametric quantile estimation using surrogate models and importance sampling

Cites Work

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• New approaches to nonparametric density estimation and selection of smoothing parameters
• A Berry-Esseen theorem for sample quantiles under weak dependence
• Asymptotic normality of the kernel quantile estimator
• Fourier and Hermite series estimates of regression functions
• Application of Bernstein polynomials for smooth estimation of a distribution and density function
• On the distribution of the clipping median under a mixture model
• On the accuracy of the normal approximation for quantiles
• A distribution-free theory of nonparametric regression
• Strong approximation of the empirical process of GARCH sequences
• The Bernstein polynomial estimator of a smooth quantile function
• Coherent Measures of Risk
• Polynomial and spline estimators of the distribution function with prescribed accuracy
• Asymptotic expansions for sums of weakly dependent random vectors
• Probability for Statisticians
• Probability: A Graduate Course
• Bootstrapping rank statistics.

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