Asymptotic normality of the recursive kernel regression estimate under dependence conditions
type: Item
instance of: scholarly article
title: Asymptotic normality of the recursive kernel regression estimate under dependence conditions
zbMATH Open document ID: 0925.62171
author: George Roussas
author: Lanh Tat Tran
published in: The Annals of Statistics
publication date: 1992-09-27T00:00:00Z
review text: Let \(\{(X_i,Y_i)\}_{i\geq 1}\) be a strictly stationary and \(\alpha\)-mixing stochastic process, where \(X_i\) and \(Y_i\) are \(d\)- and one-dimensional random variables, resp. The authors study the limit behavior of certain recursive kernel estimators of the conditional expectation \(m(x) = E(Y_1| X_1=x), x\in R^d\).
Mathematics Subject Classification ID: 62G20
Mathematics Subject Classification ID: 62G07
zbMATH DE Number: 61831
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1176348514
OpenAlex ID: W2048552588
DOI: 10.1214/AOS/1176348514
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description: scientific article; zbMATH DE number 61831