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Reduce computation in profile empirical likelihood method

  • Li, Minqiang
  • Peng, Liang
  • Qi, Yongcheng

Since its introduction by Owen in [29, 30], 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 [35]. 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 paper we propose a jackknife empirical likelihood method to overcome this computational burden. This proposed method is easy to implement and works well in practice.

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File URL: http://mpra.ub.uni-muenchen.de/33744/1/MPRA_paper_33744.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 33744.

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Date of creation: 2011
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Handle: RePEc:pra:mprapa:33744
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