Diagnostics for skew-normal nonlinear regression models with AR(1) errors

被引：32
|
作者：
Xie, Feng-Chang [1 ,2 ]
Lin, Jin-Guan [1 ]
Wei, Bo-Cheng [1 ]
机构：
[1] Southeast Univ, Dept Math, Nanjing 210096, Peoples R China
[2] Nanjing Agr Univ, Dept Math, Nanjing 210095, Peoples R China
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2009年 / 53卷 / 12期
关键词：
HETEROSCEDASTICITY; LIKELIHOOD; INFERENCE; TESTS;
D O I：
10.1016/j.csda.2009.06.010
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this article, we consider some diagnostics for skew-normal nonlinear regression models with AR(1) errors which provide a useful extension of the normal regression models. The estimation of the parameters in the models is studied based on the EM algorithm. Meanwhile, several score tests are presented for testing the homogeneity of the scale parameter and/or significance of autocorrelation in skew-normal nonlinear regression models. The properties of score tests are investigated through Monte Carlo simulations. The test methods are illustrated with two numerical examples. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码：4403 / 4416
页数：14
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