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Empirical likelihood for partially time-varying coefficient models with dependent observations

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  • Guo-Liang Fan
  • Han-Ying Liang
  • Zhen-Sheng Huang

Abstract

In this paper, we apply the empirical likelihood method to study the partially time-varying coefficient models with a random design and a fixed design under dependent assumptions. A nonparametric version of Wilks’ theorem is derived for the fixed-design case. For the random-design case, it is proved that the empirical log-likelihood ratio of the regression parameters admits a limiting distribution with a weighted sum of independent chi-squared distributions. In order that Wilks’ phenomenon holds, we propose an adjusted empirical log-likelihood (ADEL) ratio for the regression parameters. The ADEL is shown to have a standard chi-squared limiting distribution. Simulation studies are undertaken to indicate that the proposed methods work better than the normal approximation-based approach.

Suggested Citation

  • Guo-Liang Fan & Han-Ying Liang & Zhen-Sheng Huang, 2012. "Empirical likelihood for partially time-varying coefficient models with dependent observations," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 71-84.
    • Handle: RePEc:taf:gnstxx:v:24:y:2012:i:1:p:71-84
    DOI: 10.1080/10485252.2011.626411
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    References listed on IDEAS

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