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Reduce computation in profile empirical likelihood method

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

Abstract

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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Bibliographic Info

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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Keywords: profile empirical likelihood; estimating equation; Jackknife;

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Cited by:
  1. Zhang, Rongmao & Peng, Liang & Qi, Yongcheng, 2012. "Jackknife-blockwise empirical likelihood methods under dependence," Journal of Multivariate Analysis, Elsevier, vol. 104(1), pages 56-72, February.

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