On consistency of the weighted estimator in nonparametric regression model with asymptotically almost negatively associated random variables

DOI10.1080/03610926.2020.1871018OpenAlexW3119304476MaRDI QIDQ5104514

Ping Chen, Liwang Ding

Publication date: 14 September 2022

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

Full work available at URL: https://doi.org/10.1080/03610926.2020.1871018

zbMATH Keywords

strong consistencynonparametric regression modelcomplete consistencyasymptotically almost negatively associated random variables

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Foundations of stochastic processes (60G05)

Related Items (1)

Complete q-th moment convergence for the maximum of partial sums of m-negatively associated random variables and its application to the EV regression model^*

Cites Work

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• The Hájek-Rényi inequality for the AANA random variables and its applications
• Complete consistency of estimators for regression models based on extended negatively dependent errors
• Rosenthal type inequalities for asymptotically almost negatively associated random variables and applications
• Consistent nonparametric regression. Discussion
• Uniformly asymptotic normality of the regression weighted estimator for negatively associated samples.
• Laws of large numbers for Cesàro alpha-integrable random variables under dependence condition AANA or AQSI
• Negative association of random variables, with applications
• The strong law of large numbers and the law of the iterated logarithm for product sums of NA and AANA random variables
• Extensions of the strong law of large numbers of Marcinkiewicz and Zygmund for dependent variables
• The strong law of large numbers for weighted averages under dependence assumptions
• On consistency of the nearest neighbor estimator of the density function and its applications
• The Berry-Esseen bounds of the weighted estimator in a nonparametric regression model
• Strong laws of large numbers for weighted sums of asymptotically almost negatively associated random variables
• Complete consistency of the estimator of nonparametric regression model under ND sequence
• Asymptotic properties for estimates of nonparametric regression models based on negatively associated sequences
• Strong convergence for sequences of asymptotically almost negatively associated random variables
• A note on the consistency of wavelet estimators in nonparametric regression model under widely orthant dependent random errors
• Complete Convergence and the Law of Large Numbers

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