Some inequalities for a LNQD sequence with applications

DOI10.1186/1029-242X-2012-216zbMath1280.60019OpenAlexW2134825742WikidataQ59290928 ScholiaQ59290928MaRDI QIDQ385868

Naiyi Li, Yongming Li, Jian-hua Guo

Publication date: 11 December 2013

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1186/1029-242x-2012-216

zbMATH Keywords

asymptotic normalityexponential inequalitymoment inequalitycharacteristic function inequalityLNQD sequence

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic distribution theory in statistics (62E20) Inequalities; stochastic orderings (60E15)

Related Items (7)

Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples ⋮ The asymptotic normality of the linear weighted estimator in nonparametric regression models ⋮ On the linearly extended negative quadrant dependent random variables and its inequalities ⋮ Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence ⋮ The law of the iterated logarithm for LNQD sequences ⋮ The Berry--Esseen Bound for $\rho$-Mixing Random Variables and Its Applications in Nonparametric Regression Model ⋮ Asymptotic normality and mean consistency for the weighted estimator in nonparametric regression models

Cites Work

• Mean convergence theorems and weak laws of large numbers for weighted sums of dependent random variables
• Negative association of random variables, with applications
• Exponential inequalities and complete convergence for a LNQD sequence
• Maximal moment inequality for partial sums of strong mixing sequences and application
• EXPONENTIAL PROBABILITY INEQUALITY FOR LINEARLY NEGATIVE QUADRANT DEPENDENT RANDOM VARIABLES
• Some Concepts of Dependence
• A functional central limit theorem for asymptotically negatively dependent random fields

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