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Activity Number: 504
Type: Contributed
Date/Time: Thursday, August 10, 2006 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #306785
Title: Empirical Bayes Analysis on the Power Law Process
Author(s): Zhao Chen*+
Companies: Florida Gulf Coast University
Address: Department of Physics and Math CAS, Fort Myers, FL, 33965-6565,
Keywords: empirical Bayes ; power law process ; natural conjugate prior
Abstract:

The power law process has been used extensively in software reliability growth models. In our study, we focus on Empirical Bayes (EB) analysis on the power law process by employing parametric EB priors and nonparametric EB priors. For the parametric priors, we apply two-hyperparameter natural conjugate prior and a more generalized three-hyperparameter natural conjugate prior. We also make comparison with Bayesian approach. Since we have past experience about the parameters of the model, we can employ data to estimate the hyperparameters of priors, hence estimate the priors in parametric empirical Bayes.

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