Nonparametric relative recursive regression estimators for censored data

DOI10.1080/15326349.2020.1828101zbMath1466.62279OpenAlexW3092214487MaRDI QIDQ4988562

Yousri Slaoui

Publication date: 17 May 2021

Published in: Stochastic Models (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15326349.2020.1828101

zbMATH Keywords

bandwidth selectioncensored datastochastic approximation algorithmrelative regression estimation

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Censored data models (62N01) Stochastic approximation (62L20)

Related Items (1)

Bernstein polynomial of recursive regression estimation with censored data

Cites Work

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• Nonparametric relative regression for associated random variables
• Relative error prediction via kernel regression smoothers
• Practical bandwidth selection in deconvolution kernel density estimation
• The stochastic approximation method for the estimation of a multivariate probability density
• Almost sure approximations to the Robbins-Monro and Kiefer-Wolfowitz processes with dependent noise
• Nonparametric regression analysis of longitudinal data
• General convergence results for stochastic approximations via weak convergence theory
• Strong convergence of a stochastic approximation algorithm
• Relative-error prediction
• Optimal bandwidth selection for semi-recursive kernel regression estimators
• Functional limit laws for the increments of Kaplan-Meier product-limit processes and applications
• Nonparametric and semiparametric models.
• Recursive density estimators based on Robbins-Monro's scheme and using Bernstein polynomials
• Bandwidth selection for recursive kernel density estimators defined by stochastic approximation method
• The stochastic approximation method for estimation of a distribution function
• Recursive kernel density estimation and optimal bandwidth selection under \(\alpha\): mixing data
• Nonparametric relative regression under random censorship model
• Fundamental-series representations of a semisimple Lie group
• A unified theory of regularly varying sequences
• Nonparametric Estimation from Incomplete Observations
• 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
• How to apply the method of stochastic approximation in the non-parametric estimation of a regression function¹
• Recursive kernel density estimators under missing data
• Recursive distribution estimator defined by stochastic approximation method using Bernstein polynomials
• Bias reduction in kernel density estimation
• Bayesian adaptive bandwidth selector for multivariate discrete kernel estimator
• Applied Nonparametric Econometrics
• Regularly Varying Sequences
• A Stochastic Approximation Method
• Plug‐in bandwidth selector for recursive kernel regression estimators defined by stochastic approximation method

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