Spurious functional-coefficient regression models and robust inference with marginal integration

2021 ◽  
Author(s):  
Yundong Tu ◽  
Ying Wang
Keyword(s):  
Regression Models ◽  
Robust Inference ◽  
Marginal Integration ◽  
Functional Coefficient

scholarly journals Model-robust inference for continuous threshold regression models

Biometrics ◽  
2016 ◽  
Vol 73 (2) ◽  
pp. 452-462 ◽  
Author(s):  
Youyi Fong ◽  
Chongzhi Di ◽  
Ying Huang ◽  
Peter B. Gilbert
Keyword(s):  
Regression Models ◽  
Robust Inference ◽  
Threshold Regression

scholarly journals QML Estimators in Linear Regression Models with Functional Coefficient Autoregressive Processes

2010 ◽  
Vol 2010 ◽  
pp. 1-30 ◽  
Author(s):  
Hongchang Hu
Keyword(s):  
Maximum Likelihood ◽  
Linear Regression ◽  
Regression Models ◽  
Asymptotic Properties ◽  
Asymptotic Distributions ◽  
Autoregressive Processes ◽  
Linear Regression Models ◽  
Unknown Parameters ◽  
Quasi Maximum Likelihood ◽  
Functional Coefficient

This paper studies a linear regression model, whose errors are functional coefficient autoregressive processes. Firstly, the quasi-maximum likelihood (QML) estimators of some unknown parameters are given. Secondly, under general conditions, the asymptotic properties (existence, consistency, and asymptotic distributions) of the QML estimators are investigated. These results extend those of Maller (2003), White (1959), Brockwell and Davis (1987), and so on. Lastly, the validity and feasibility of the method are illuminated by a simulation example and a real example.

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