Recursive kernel estimator in a semiparametric regression model

DOI10.1080/10485252.2022.2130308OpenAlexW4304087058MaRDI QIDQ5881429

Emmanuel de Dieu Nkou

Publication date: 10 March 2023

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

Full work available at URL: https://doi.org/10.1080/10485252.2022.2130308

zbMATH Keywords

asymptotic normalitydimension reductionsemiparametric regressionsliced inverse regressionrecursive kernel estimators

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05) General nonlinear regression (62J02) Nonparametric inference (62Gxx)

Cites Work

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• A new approach on recursive and non-recursive SIR methods
• Asymptotics for sliced average variance estimation
• On a parametric family of sequential estimators of the density for a strong mixing process
• The stochastic approximation method for the estimation of a multivariate probability density
• Consistent estimation of the dimensionality in sliced inverse regression
• An asymptotically optimal window selection rule for kernel density estimates
• Slicing regression: A link-free regression method
• Asymptotics for kernel estimate of sliced inverse regression
• Bandwidth selection for recursive kernel density estimators defined by stochastic approximation method
• On kernel method for sliced average variance estimation
• A companion for the Kiefer-Wolfowitz-Blum stochastic approximation algorithm
• Compact Law of the Iterated Logarithm for Matrix-Normalized Sums of Random Vectors
• Revisiting R\'ev\'esz's stochastic approximation method for the estimation of a regression function
• Sliced Inverse Regression for Dimension Reduction
• How to apply the method of stochastic approximation in the non-parametric estimation of a regression function¹
• Graphics for Regressions With a Binary Response
• Semiparametric Estimation of Index Coefficients
• Wavelet-based estimation in a semiparametric regression model
• Strong consistency of kernel estimator in a semiparametric regression model
• Large and moderate deviation principles for recursive kernel density estimators defined by stochastic approximation method
• Asymptotically optimal discriminant functions for pattern classification
• Regularly Varying Sequences
• A Note on Permanents
• Comment
• Sliced inverse regression (SIR): An appraisal of small sample alternatives to slicing

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