Empirical Bayes Analysis on the Power Law Process with Natural Conjugate Priors

10.6339/JDS.2010.08(1).552

Zhao Chen

Empirical Bayes ； natural conjugate prior ； power law process

Journal of Data Science

8卷1期（2010 / 01 / 01）

139 - 149

英文

The power law process has been used extensively in software reliability models, reliability growth models and more generally reliable systems. In this paper we work on the Power Law Process via empirical Bayes (EB) approach. Based on a two-hyperparameter natural conjugate prior and a more generalized three-hyperparameter natural conjugate prior, which was stated in Huang and Bier (1998), we work out an empirical Bayes (EB) procedure and provide statistical inferences based on the natural conjugate priors. Given past experience about the parameters of the model, the empirical Bayes (EB) approach uses the observed data to estimate the hyperparamters of priors and then proceeds as though the prior were known.