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Activity Number: 184
Type: Contributed
Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract - #307766
Title: Best Power-Divergence Confidence Interval for a Binomial Proportion
Author(s): Shaobo Jin*+
Companies: Uppsala University
Keywords: Power-divergence family ; Confidence interval ; Binomial proportion ; Edgeworth expansion

The confidence interval for a binomial proportion based on the power-divergence family is considered in this paper. The properties of the confidence intervals are studied in detail. Several choices of the additional parameter lambda are also studied. Numerical results indicate that aligning the mean coverage probability to the nominal value may not be a suitable criterion to choose lambda for the power-divergence family. Maximizing the confidence coefficient is a good alternative which is better than some of the recommended competitors in the literature. Such lambda leads to some intervals very close to the Jeffreys interval after taking expectations to the proportion under certain Beta distributed priors. Besides, we can also control lambda and significance level simultaneously to have unbiased intervals in the long run. Edgeworth expansions for the coverage probability and expected length are also derived.

Authors who are presenting talks have a * after their name.

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