The empirical likelihood goodness-of-fit test for regression model

被引：0

作者：

Lixing ZHU Yongsong QIN Wangli XU Department of Mathematics Hong Kong Baptist University Kowloon Tong Hong Kong China

School of Mathematical Sciences Guangxi Normal Uinversity Guilin China ^{[541004
]}

School of Statistics Renmin University of China Beijing China ^{[100875
]}

机构：

来源：

ScienceinChina(SeriesA:Mathematics) | 2007年 / 06期

关键词：

regression model; AR time series models; empirical likelihood; asymptotic normality; goodness-of-fit;

D O I：

暂无

中图分类号：

O212.7 [非参数统计];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

<正>Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology.

引用

页码：829 / 840

页数：12