Laws of large numbers and complete convergence for WOD random variables and their applications

DOI10.1080/03610918.2020.1851714OpenAlexW3111239411MaRDI QIDQ6171288

Chi Yao, Rui Wang, Xue-jun Wang, Yongping He

Publication date: 17 July 2023

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2020.1851714

zbMATH Keywords

complete convergencenonparametric regression modelwidely orthant dependent random variables\(L_r\) convergence\(h\)-integrability

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Strong limit theorems (60F15) (L^p)-limit theorems (60F25)

Cites Work

• Unnamed Item
• Unnamed Item
• Exponential probability inequalities for WNOD random variables and their applications
• An inequality of widely dependent random variables and its applications
• Basic renewal theorems for random walks with widely dependent increments
• Complete consistency of estimators for regression models based on extended negatively dependent errors
• Complete and complete moment convergence for weighted sums of widely orthant dependent random variables
• Precise large deviations for dependent random variables with heavy tails
• Consistent nonparametric multiple regression: the fixed design case
• Fixed design regression for time series: Asymptotic normality
• Consistent nonparametric regression. Discussion
• A connection between supermodular ordering and positive/negative association.
• Complete moment convergence for arrays of rowwise widely orthant dependent random variables
• Weak and strong laws of large numbers for arrays of rowwise END random variables and their applications
• Convergence in \(r\)-mean of weighted sums of NQD random variables
• Mean convergence theorems and weak laws of large numbers for weighted sums of random variables under a condition of weighted integrability
• Negative association of random variables, with applications
• Uniform asymptotics for the finite-time ruin probability of a dependent risk model with a constant interest rate
• Bernstein-type inequality for widely dependent sequence and its application to nonparametric regression models
• On complete convergence for widely orthant-dependent random variables and its applications in nonparametric regression models
• Complete consistency of the estimator of nonparametric regression model under ND sequence
• Weak laws of large numbers for arrays of dependent random variables
• On the Bahadur representation of sample quantiles for widely orthant dependent sequences
• Complete convergence for arrays of rowwise widely orthant dependent random variables and its applications
• WEAK LAWS OF LARGE NUMBERS FOR ARRAYS UNDER A CONDITION OF UNIFORM INTEGRABILITY
• Some Concepts of Dependence
• Fixed-design regression for linear time series

This page was built for publication: Laws of large numbers and complete convergence for WOD random variables and their applications