Optimal constrained confidence estimation via tail functions

Borek D. Puza, Terence O'Neill

Research output: Contribution to journalArticleResearchpeer-review

Abstract

This paper focuses on confidence estimation for constrained parameters. It is shown how the method of tail functions can be used to engineer a constrained confidence interval which is optimal in terms of prior expected length. The strategy is compared with the unified approach of Feldman and Cousins (1998) and illustrated by application to inference on the normal mean.
Original languageEnglish
Pages (from-to)134-140
Number of pages7
JournalMathematical Scientist
Volume33
Issue number2
Publication statusPublished - 2008

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Optimal constrained confidence estimation via tail functions. / Puza, Borek D.; O'Neill, Terence.

In: Mathematical Scientist, Vol. 33, No. 2, 2008, p. 134-140.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Puza, Borek D.

AU - O'Neill, Terence

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AB - This paper focuses on confidence estimation for constrained parameters. It is shown how the method of tail functions can be used to engineer a constrained confidence interval which is optimal in terms of prior expected length. The strategy is compared with the unified approach of Feldman and Cousins (1998) and illustrated by application to inference on the normal mean.

M3 - Article

VL - 33

SP - 134

EP - 140

JO - Mathematical Scientist

JF - Mathematical Scientist

SN - 0312-3685

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