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Activity Number: 486 - Computing Kaleidoscope
Type: Contributed
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:12 AM
Sponsor: Section on Statistical Computing
Abstract #329895 Presentation
Title: Nearly Best Confidence Intervals
Author(s): George Terrell*
Companies: VA Poly. Inst. & State Univ.
Keywords: Confidence Intervals; Estimation; Small-Sample Asymptotics

A confidence interval for a parameter theta is a range of values determined by experimental information that has a certain 1 minus alpha probability of covering the true value of that parameter. The coverage probability determines only one of the limits of an interval. The best way to determine the other limit is the condition Likelihood(theta) > = c(alpha). In unsymmetric families, this has no simple formula and must usually be found numerically. We here propose closed-form approximations to the limits in several important families.

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

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