Weighted sums of strongly mixing random variables with an application to nonparametric regression

DOI10.1016/j.spl.2015.05.022zbMath1328.60087OpenAlexW886550236MaRDI QIDQ894597

Le Van Thanh, G. George Yin

Publication date: 1 December 2015

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2015.05.022

zbMATH Keywords

complete convergencenonparametric regressionweighted sumstrongly mixing process

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Strong limit theorems (60F15)

Related Items (5)

The Berry–Esseen-type bound for the G-M estimator in a nonparametric regression model with α-mixing errors ⋮ Capacity inequalities and strong laws for \(m\)-widely acceptable random variables under sub-linear expectations ⋮ Marcinkiewicz–Zygmund type strong law of large numbers for weighted sums of random variables with infinite moment and its applications ⋮ Strong convergence for weighted sums of widely orthant dependent random variables and applications ⋮ Strong laws for weighted sums of \(m\)-extended negatively dependent random variables and its applications

Cites Work

• The consistency for estimator of nonparametric regression model based on NOD errors
• Convergence rates in the strong law for bounded mixing sequences
• Consistent nonparametric multiple regression: the fixed design case
• Fixed design regression for time series: Asymptotic normality
• Complete convergence for \(\alpha{}\)-mixing sequences
• Almost-sure results for a class of dependent random variables
• Maximal inequalities for partial sums of \(\rho\)-mixing sequences
• A note on the rates of convergence for weighted sums of \(\rho^\ast\)-mixing random variables
• On the strong convergence for weighted sums of \(\rho ^{*}\)-mixing random variables
• On the subspaces of \(L^p\) \((p > 2)\) spanned by sequences of independent random variables
• On the Rate of Complete Convergence for Weighted Sums of Arrays of Rowwise ϕ-Mixing Random Variables
• State Observers with Random Sampling Times and Convergence Analysis of Double-Indexed and Randomly Weighted Sums of Mixing Processes
• On Strong Mixing Conditions for Stationary Gaussian Processes
• On complete convergence for strong mixing sequences
• Convergence Rates in the Law of Large Numbers
• Complete Convergence and the Law of Large Numbers
• On a Theorem of Hsu and Robbins

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