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Semiparametric Empirical Likelihood for Circular Distributions

In: Recent Advances in Econometrics and Statistics

Author

Listed:
  • Yan Liu

    (Waseda University)

  • Lan Wu

    (Waseda University)

  • Masanobu Taniguchi

    (Waseda University)

Abstract

A new family of circular distributions has been proposed as circular distributions generated from general spectral densities of time series models. These circular models have shown promising potential for analyzing and interpreting circular data. However, a significant challenge arises in the statistical inference for those circular data due to the loss of explicit forms associated with the normalizing constants in these circular models. We consider the empirical likelihood for data coming from these circular distributions. The proposed empirical likelihood ratio test has a chi-squared limiting distribution. The theoretical results are illustrated by numerical simulations and real data analysis.

Suggested Citation

  • Yan Liu & Lan Wu & Masanobu Taniguchi, 2024. "Semiparametric Empirical Likelihood for Circular Distributions," Springer Books, in: Matteo Barigozzi & Siegfried Hörmann & Davy Paindaveine (ed.), Recent Advances in Econometrics and Statistics, pages 597-618, Springer.
  • Handle: RePEc:spr:sprchp:978-3-031-61853-6_30
    DOI: 10.1007/978-3-031-61853-6_30
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