Testing Serial Correlation in Partially Linear Additive Models

查看全文 作　　者：Jin [1,2]YANG;Chuan-hua [3]WEI

机构地区：[1]School of Statistics and Data Science,Nankai University;[2]Department of Applied Mathematics,The Hong Kong Polytechnic University;[3]Department of Statistics,School of Science,Minzu University of China

出　　处：《Acta Mathematicae Applicatae Sinica》索引2019年第35卷第2期,共11页

基　　金：Chuanhua Wei’s research was supported by the National Natural Science Foundation of China(11301565);Jin Yang’s research was supported by the Post-doctoral Fellowship of Nankai University 摘　　要：As an extension of partially linear models and additive models, partially linear additive model is useful in statistical modelling. This paper proposes an empirical likelihood based approach for testing serial correlation in this semiparametric model. The proposed test method can test not only zero first-order serial correlation, but also higher-order serial correlation. Under the null hypothesis of no serial correlation, the test statistic is shown to follow asymptotically a chi-square distribution. Furthermore, a simulation study is conducted to illustrate the performance of the proposed method. 关键词：PARTIALLY LINEAR additive model BACKFITTING Profile LEAST-SQUARES approach Empirical LIKELIHOOD SERIAL correlation

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Testing Serial Correlation in Partially Linear Additive Models

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