Weak convergence for weighted sums of negatively associated random variables and its application in nonparametric regression models

DOI10.1080/03610918.2020.1784431OpenAlexW3037143508MaRDI QIDQ5042173

Jibing Qi, Lu Zhang, Hairong Yang, Xue-jun Wang

Publication date: 18 October 2022

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

Full work available at URL: https://doi.org/10.1080/03610918.2020.1784431

zbMATH Keywords

convergence rateweak consistencyweak law of large numbersnegatively associated random variablesnonparametric regression models

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05)

Related Items

Weak convergence for weighted sums of a class of random variables with related statistical applications ⋮ Weak consistency for the estimators in a semiparametric regression model based on negatively associated random errors

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Asymptotic normality of conditional density estimation with left-truncated and dependent data
• Complete consistency of estimators for regression models based on extended negatively dependent errors
• Exponential inequality for negatively associated random variables
• Consistent nonparametric multiple regression for dependent heterogeneous processes: the fixed design case
• Consistent regression estimation with fixed design points under dependence conditions
• Fixed design regression for time series: Asymptotic normality
• Consistent nonparametric regression. Discussion
• A comparison theorem on moment inequalities between negatively associated and independent random variables
• Asymptotic normality of the kernel estimate of a probability density function under association
• Negative association of random variables, with applications
• Complete convergence for moving average processes associated to heavy-tailed distributions and applications
• Complete moment and integral convergence for sums of negatively associated random variables
• Applications of the Rosenthal-type inequality for negatively superadditive dependent random variables
• A law of the iterated logarithm of partial sums for NA random variables
• 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
• Asymptotic properties for estimates of nonparametric regression models based on negatively associated sequences
• Complete convergence for weighted sums of END random variables and its application to nonparametric regression models
• COMPLETE MOMENT CONVERGENCE FOR ARRAYS OF ROWWISE NEGATIVELY ASSOCIATED RANDOM VARIABLES AND ITS APPLICATION IN NON-PARAMETRIC REGRESSION MODEL
• Convergence rates in the weak law of large numbers for weighted sums of i.i.d. random variables and applications in errors-in-variables models
• THE CONSISTENCY FOR THE WEIGHTED ESTIMATOR OF NON-PARAMETRIC REGRESSION MODEL BASED ON WIDELY ORTHANT-DEPENDENT ERRORS
• Convergence Rates in the Law of Large Numbers
• A Note on the Weak Law
• Fixed-design regression for linear time series
• Fixed-design regression for linear time series