Reduce computation in profile empirical likelihood method

Minqiang Li, Liang Peng, Yongcheng Qi

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Since its introduction by Owen (1988, 1990), the empirical likelihood method has been extensively investigated and widely used to construct confidence regions and to test hypotheses in the literature. For a large class of statistics that can be obtained via solving estimating equations, the empirical likelihood function can be formulated from these estimating equations as proposed by Qin and Lawless (1994). If only a small part of parameters is of interest, a profile empirical likelihood method has to be employed to construct confidence regions, which could be computationally costly. In this article the authors propose a jackknife empirical likelihood method to overcome this computational burden. This proposed method is easy to implement and works well in practice.

Original languageEnglish (US)
Pages (from-to)370-384
Number of pages15
JournalCanadian Journal of Statistics
Issue number2
StatePublished - Jun 2011


  • Estimating equation
  • Jackknife
  • Profile empirical likelihood


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