Testing Serial Correlation in Partially Linear Additive Models
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  • 英文篇名：Testing Serial Correlation in Partially Linear Additive Models
  • 作者：Jin ; YANG ; Chuan-hua ; WEI
  • 英文作者：Jin YANG;Chuan-hua WEI;School of Statistics and Data Science,Nankai University;Department of Applied Mathematics,The Hong Kong Polytechnic University;Department of Statistics,School of Science,Minzu University of China;
  • 英文关键词：Partially linear additive model;;Backfitting;;Profile least-squares approach;;Empirical likelihood;;Serial correlation
  • 中文刊名：YISY
  • 英文刊名：应用数学学报(英文版)
  • 机构：School of Statistics and Data Science,Nankai University;Department of Applied Mathematics,The Hong Kong Polytechnic University;Department of Statistics,School of Science,Minzu University of China;
  • 出版日期：2019-04-15
  • 出版单位：Acta Mathematicae Applicatae Sinica
  • 年：2019
  • 期：v.35
  • 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
  • 语种：英文;
  • 页：YISY201902012
  • 页数：11
  • CN：02
  • ISSN：11-2041/O1
  • 分类号：151-161
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.
        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.
引文
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