Almost sure convergence of recursive kernel estimatiors of the density and the regression under η− weak dependence

DOI10.1080/03610926.2019.1710751OpenAlexW3004393490MaRDI QIDQ5078876

Mezhoud Kenza Assia

Publication date: 25 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2019.1710751

zbMATH Keywords

rates of convergencealmost sure convergence\(\eta\)-weak dependencerecursive kernel estimatesdensity and regression

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Recursive kernel estimation of the density under \(\eta\)-weak dependence
• Probability and moment inequalities for sums of weakly dependent random variables, with applications
• Strong uniform convergence of the recursive regression estimator under \(\phi\)-mixing conditions.
• Remarks on some recursive estimators of a probability density
• A new weak dependence condition and applications to moment inequalities
• Optimal global rates of convergence for nonparametric regression
• Weak dependence beyond mixing and asymptotics for nonparametric regression
• Functional Estimation of a Density Under a New Weak Dependence Condition
• On the L 1 convergence of kernel estimators of regression functions with applications in discrimination
• Recursive density estimation under dependence

This page was built for publication: Almost sure convergence of recursive kernel estimatiors of the density and the regression under η− weak dependence