Abstract #301487

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JSM 2003 Abstract #301487
Activity Number: 173
Type: Contributed
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Stat. Sciences
Abstract - #301487
Title: Analysis of Cepheid Star Oscillations with Expected Posterior Priors
Author(s): German R. Molina*+ and James O. Berger
Companies: Duke University and Duke University
Address: 222 Old Chem Bldg., ISDS, Durham, NC, 27708-0251,
Keywords: Bayesian ; expected posterior priors
Abstract:

In model selection problems, we might not be able to construct a proper prior for paramaters that are not common for different models. We use of expected posterior priors to overcome this problem by using minimal training samples from the available data. We construct proper priors that are meaningful across models and can still be used for model comparisons. Our model selection problem involves a Fourier analysis of Cepheid stars data with an unknown number of Fourier coefficients. Movements in the model space are performed using an independence sampler jointly moving over the model, parameter and training sample spaces. Comparisons with the g-Prior-based results are provided.

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