Bayesian Estimation of Change Point of Burr Type III Distribution under Precautionary Loss Function

Alterations or sudden changes within a sequence of temporal observations always create disturbance to data analysis. The problem to detect this alterations or changes in any temporal data may allow researchers to identify the abnormality in every sequence. The Bayesian method proposed by Basu and Ebrahimi (1991) have greatly plays important role to find the Bayes Estimators of the parameters of any sequence and analysis of change point problems through Bayesian Technique. In this paper Bayes estimators the Change point and the parameters of Burr type III distribution are obtained under Precautionary Loss Function using Inverted Gamma Prior as natural conjugate prior. We study Bayesian analysis for change point problem with R programming. The result provides accurate change point and posterior means estimation.