The strong consistency of the estimator of fixed-design regression model under negatively dependent sequences

DOI10.1155/2013/521618zbMath1364.62100OpenAlexW2032933993WikidataQ58916997 ScholiaQ58916997MaRDI QIDQ2015698

Shuhe Hu, Meimei Ge, Xize Wang, Xue-jun Wang

Publication date: 23 June 2014

Published in: Abstract and Applied Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/521618

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items (1)

Applications of the Rosenthal-type inequality for negatively superadditive dependent random variables

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Some strong limit theorems for arrays of rowwise negatively orthant-dependent random variables
• A complete convergence theorem for weighted sums of arrays of rowwise negatively dependent random variables
• The consistency for estimator of nonparametric regression model based on NOD errors
• On the strong convergence rate for weighted sums of arrays of rowwise negatively orthant dependent random variables
• Complete convergence for weighted sums of negatively dependent random variables
• Complete convergence of weighted sums under negative dependence
• Complete convergence for weighted sums of sequences of negatively dependent random variables
• An exponential inequality for a NOD sequence and a strong law of large numbers
• Consistent nonparametric multiple regression for dependent heterogeneous processes: the fixed design case
• Complete convergence for negatively dependent sequences of random variables
• Weak and universal consistency of moving weighted averages
• Nonparametric function recovering from noisy observations
• Consistent nonparametric multiple regression: 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 negatively dependent random variables
• Negative association of random variables, with applications
• Complete convergence for arrays of rowwise negatively orthant dependent random variables
• Strong and weak convergence for asymptotically almost negatively associated random variables
• A strong limit theorem for weighted sums of sequences of negatively dependent random variables
• Exponential inequalities and inverse moment for NOD sequence
• Bernstein-type inequality for widely dependent sequence and its application to nonparametric regression models
• On the almost sure growth rate of sums of lower negatively dependent nonnegative random variables
• Asymptotic properties for estimates of nonparametric regression models based on negatively associated sequences
• Some strong limit theorems of weighted sums for negatively dependent generalized Gaussian random variables
• A strong law of large numbers for arrays of rowwise negatively dependent random variables
• On Some Conditions for Complete Convergence for Arrays of Rowwise Negatively Dependent Random Variables
• The Hajeck-Renyi inequality for weighted sums of negatively orthant dependent random variables
• The Strong Law of Large Numbers for Negatively Dependent Generalized Gaussian Random Variables
• Some Concepts of Dependence
• ALMOST SURE CONVERGENCE FOR WEIGHTED SUMS OF NEGATIVELY ORTHANT DEPENDENT RANDOM VARIABLES
• Fixed-design regression for linear time series
• Fixed-design regression for linear time series

This page was built for publication: The strong consistency of the estimator of fixed-design regression model under negatively dependent sequences