Abstract #300547


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JSM 2002 Abstract #300547
Activity Number: 284
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Stat. Sciences*
Abstract - #300547
Title: Approximate Bayesian Confidence Intervals for the Variance of a Gaussian Distribution
Author(s): Vincent Camara*+
Affiliation(s): University of South Florida
Address: 8799 Bardmoor Blvd., Unit 201, Largo, Florida, 33777, USA
Keywords: Estimation ; Loss functions ; Statistical analysis
Abstract:

The aim of the present study is to obtain and compare confidence intervals for the variance of a Gaussian distribution. Considering respectively the square error and the Higgins-Tsokos loss functions, approximate Bayesian confidence intervals for the variance of a normal population are derived. Using normal data and SAS software, the obtained approximate Bayesian confidence intervals will then be compared to the ones obtained with the well-known classical method.

It is shown that the proposed Bayesian approach relies only on the observations. The classical method, which uses the Chi-square statistic, does not always yield the best confidence intervals. In fact, the proposed approach performs often better.


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