The large deviation results for the nonlinear regression model with dependent errors

DOI10.1007/s11749-016-0509-zOpenAlexW2556994683MaRDI QIDQ1694368

Wenzhi Yang, Zhangrui Zhao, Xinghui Wang, Shuhe Hu

Publication date: 1 February 2018

Published in: Test (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11749-016-0509-z

zbMATH Keywords

large deviationleast squares estimatornonlinear regression modelsEND random variables

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) General nonlinear regression (62J02)

Related Items (2)

Asymptotic properties of LS estimator in nonlinear functional EV models ⋮ Complete convergence of randomly weighted END sequences and its application

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A large deviation result for the least squares estimators in nonlinear regression
• The rate of convergence for the least squares estimator in nonlinear regression model with dependent errors.
• Consistency for the least squares estimator in nonlinear regression model
• Complete convergence theorems for extended negatively dependent random variables
• The Strong Law of Large Numbers for Extended Negatively Dependent Random Variables
• Asymptotic results on nonlinear approximation of regression functions and weighted least squares
• An Asymptotic Expansion for the Distribution of the Least Squares Estimator of the Non-Linear Regression Parameter

This page was built for publication: The large deviation results for the nonlinear regression model with dependent errors