Empirical likelihood-based serial correlation testing in partially varying coefficient single-index models

Jianbo Li, Yuan Li, Zhensheng Huang and Riquan Zhang

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 15, 4471-4485

Abstract: Partially varying coefficient single-index models (PVCSIM) are a class of semiparametric regression models. One important assumption is that the model error is independently and identically distributed, which may contradict with the reality in many applications. For example, in the economical and financial applications, the observations may be serially correlated over time. Based on the empirical likelihood technique, we propose a procedure for testing the serial correlation of random error in PVCSIM. Under some regular conditions, we show that the proposed empirical likelihood ratio statistic asymptotically follows a standard χ2 distribution. We also present some numerical studies to illustrate the performance of our proposed testing procedure.

Date: 2016
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DOI: 10.1080/03610926.2014.921306

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