Necessary and sufficient consistency conditions for a recursive kernel regression estimate

DOI10.1016/0047-259X(87)90178-3zbMath0627.62040OpenAlexW2070045967WikidataQ118592634 ScholiaQ118592634MaRDI QIDQ1092555

Włodzimierz Greblicki, Mirosław Pawlak

Publication date: 1987

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0047-259x(87)90178-3

zbMATH Keywords

consistencycomplete convergenceindependent observationsregression functionrecursive kernel estimatestrongly pointwise consistentweakly pointwise consistent

Mathematics Subject Classification ID

Nonparametric estimation (62G05)

Related Items (11)

Recursive regression estimators with application to nonparametric prediction ⋮ On the strong universal consistency of a recursive regression estimate by Pál Révész ⋮ Asymptotic normality of recursive estimators under strong mixing conditions ⋮ Consistencia de un estimador no parametrico, recursivo, de la regresion bajo condiciones generales ⋮ Nonparametric semirecursive identification in a wide sense of strong mixing processes ⋮ A simple scheme for semi-recursive identification of Hammerstein system nonlinearity by Haar wavelets ⋮ On the almost everywhere properties of the kernel regression estimate ⋮ Recursive nonparametric identification of Hammerstein systems ⋮ Recurrent nonparametric estimation of functions from functionals of multidimensional density and their derivatives ⋮ Asymptotic normality for \(L_1\) norm kernel estimator of conditional median under \(\alpha\)-mixing dependence ⋮ Recursive local polynomial regression under dependence conditions

Cites Work

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• Distribution-free pointwise consistency of kernel regression estimate
• On the almost everywhere convergence of nonparametric regression function estimates
• Consistent nonparametric regression. Discussion
• Probability Inequalities for the Sum of Independent Random Variables
• Distribution-free consistency of a nonparametric kernel regression estimate and classification
• Almost everywhere convergence of a recursive regression function estimate and classification (Corresp.)
• On the L 1 convergence of kernel estimators of regression functions with applications in discrimination

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