Smooth conditional distribution estimators using Bernstein polynomials

DOI10.1016/j.csda.2017.02.005zbMath1464.62023OpenAlexW2588984272MaRDI QIDQ1654241

Alexandre Leblanc, Mohamed Belalia, Taoufik Bouezmarni

Publication date: 7 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2017.02.005

zbMATH Keywords

mean squared errorasymptotic propertiesBernstein polynomialsconditional distribution estimation

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

Related Items (5)

On the le Cam distance between Poisson and Gaussian experiments and the asymptotic properties of Szasz estimators ⋮ Rank dynamics for functional data ⋮ Complete monotonicity of multinomial probabilities and its application to Bernstein estimators on the simplex ⋮ Asymptotic properties of Bernstein estimators on the simplex ⋮ Bernstein conditional density estimation with application to conditional distribution and regression functions

Uses Software

• KernSmooth

Cites Work

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• On the asymptotic properties of the Bernstein estimator of the multivariate distribution function
• On the boundary properties of Bernstein polynomial estimators of density and distribution functions
• Two-dimensional Bernstein polynomial density estimators
• Application of Bernstein polynomials for smooth estimation of a distribution and density function
• On estimating distribution functions using Bernstein polynomials
• Local linear regression smoothers and their minimax efficiencies
• Conditional density estimation in a regression setting
• Smooth estimation of a distribution and density function on a hypercube using Bernstein polynomials for dependent random vectors
• Multivariable Model‐Building
• A bias-reduced approach to density estimation using Bernstein polynomials
• Chung–Smirnov property for Bernstein estimators of distribution functions
• Local Linear Quantile Regression
• Methods for Estimating a Conditional Distribution Function
• Preadjusted Non-Parametric Estimation of a Conditional Distribution Function
• Dimension Reduction and Adaptation in Conditional Density Estimation
• On Non-Parametric Estimates of Density Functions and Regression Curves
• Bernstein estimator for unbounded density function

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