Strong laws of large numbers for arrays of row-wise extended negatively dependent random variables with applications

DOI10.1080/10485252.2019.1688326zbMath1435.62132OpenAlexW2989721755WikidataQ126782812 ScholiaQ126782812MaRDI QIDQ5221296

João Lita da Silva

Publication date: 25 March 2020

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2019.1688326

zbMATH Keywords

strong consistencystrong laws of large numbersnonparametric estimationwidely orthant dependent random variablesBennett inequalityrow-wise extended negatively dependent arrays

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Inequalities; stochastic orderings (60E15) Strong limit theorems (60F15)

Related Items (7)

Complete convergence and complete moment convergence for maximal weighted sums of arrays of rowwise extended negatively dependent random variables with statistical applications ⋮ Complete and complete \(f\)-moment convergence for arrays of rowwise END random variables and some applications ⋮ A general result on complete f -moment convergence with its application to nonparametric regression models ⋮ Complete convergence for weighted sums of widely acceptable random variables under sublinear expectations ⋮ Complete moment convergence for randomly weighted sums of arrays of rowwise \(m_n\)-extended negatively dependent random variables and its applications ⋮ Strong consistency of LS estimators in simple linear EV regression models with WOD errors ⋮ ℒ_p-convergence for weighted sums of arrays of rowwise extended negatively dependent random variables

Cites Work

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• Exponential probability inequalities for WNOD random variables and their applications
• Almost sure convergence for weighted sums of extended negatively dependent random variables
• Complete convergence for weighted sums of negatively dependent random variables
• Limiting behavior for arrays of row-wise upper extended negatively dependent random variables
• Consistent nonparametric multiple regression for dependent heterogeneous processes: the fixed design case
• Nonparametric function recovering from noisy observations
• Consistent nonparametric multiple regression: the fixed design case
• Asymptotic properties of the multivariate Nadaraya-Watson regression function estimate: The fixed design case
• Consistent regression estimation with fixed design points under dependence conditions
• Fixed design regression for time series: Asymptotic normality
• Complete convergence for arrays
• Convergence in \(p\)-mean for arrays of row-wise extended negatively dependent random variables
• Strong laws of large numbers for arrays of row-wise independent random variables
• Uniform asymptotics for the finite-time ruin probability of a dependent risk model with a constant interest rate
• On complete convergence for widely orthant-dependent random variables and its applications in nonparametric regression models
• An Analogue of the Law of the Iterated Logarithm
• Probability Inequalities for the Sum of Independent Random Variables
• Local Properties of k-NN Regression Estimates
• Generalized exponential bounds, iterated logarithm and strong laws
• Wavelet Methods for Curve Estimation
• Probability Inequalities for Sums of Independent Random Variables
• On Estimation of a Probability Density Function and Mode

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