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A new method of calibration for the empirical loglikelihood ratio

Listed author(s):
  • Tsao, Min
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    The Chi-square calibration for the empirical loglikelihood ratio refers to the method of approximating quantiles of the finite sample distribution of the empirical loglikelihood ratio with that of the limiting Chi-square distribution. Empirical likelihood ratio confidence regions are usually computed with the Chi-square calibration. Such Chi-square calibrated confidence regions can have a serious undercoverage problem. This paper examines the undercoverage problem from a finite sample standpoint and proposes a method of calibration which approximates the finite sample distributions with a new family of distributions. The new distributions is another family of sampling distributions arising from the normal distributions and is derived through a simple finite sample similarity between the empirical and parametric likelihoods. The new method of calibration is as easy to use as the Chi-square calibration. It corrects the undercoverage problem of the Chi-square calibration and is consistently more accurate.

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    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 68 (2004)
    Issue (Month): 3 (July)
    Pages: 305-314

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    Handle: RePEc:eee:stapro:v:68:y:2004:i:3:p:305-314
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    1. Tsao, Min, 2001. "A small sample calibration method for the empirical likelihood ratio," Statistics & Probability Letters, Elsevier, vol. 54(1), pages 41-45, August.
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