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Level-specific correction for nonparametric likelihoods

Author

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  • Yukun Liu
  • Jiahua Chen
  • Ting Li

Abstract

The popular empirical likelihood method not only has a convenient chi-square limiting distribution but is also Bartlett correctable, leading to a high-order coverage precision of the resulting confidence regions. Meanwhile, it is one of many nonparametric likelihoods in the Cressie-Read power divergence family. The other likelihoods share many attractive properties but are not Bartlett correctable. In this paper, we develop a new technique to achieve the effect of being Bartlett correctable. Our technique is generally applicable to pivotal quantities with chi-square limiting distributions. Numerical experiments and an example reveal that the method is successful for several important nonparametric likelihoods.

Suggested Citation

  • Yukun Liu & Jiahua Chen & Ting Li, 2014. "Level-specific correction for nonparametric likelihoods," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 433-449, September.
    • Handle: RePEc:taf:gnstxx:v:26:y:2014:i:3:p:433-449
    DOI: 10.1080/10485252.2014.929676
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    Cited by:

    1. Nicola Lunardon & Gianfranco Adimari, 2016. "Second-order Accurate Confidence Regions Based on Members of the Generalized Power Divergence Family," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 213-227, March.

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