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Testing Serial Correlation in Partially Linear Additive Models 被引量:12

Testing Serial Correlation in Partially Linear Additive Models
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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.
出处 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2019年第2期401-411,共11页 应用数学学报(英文版)
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
关键词 PARTIALLY LINEAR additive model BACKFITTING Profile LEAST-SQUARES approach Empirical LIKELIHOOD SERIAL correlation Partially linear additive model Backfitting Profile least-squares approach Empirical likelihood Serial correlation
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