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BAYESIAN PREDICTION BASED ON RIGHT TYPE-II CENSORED SAMPLE FOR GOMPERTZ DISTRIBUTION IN THE PRESENCE OF OUTLIERS

Research Abstract

In this article, the problem of obtaining Bayesian prediction bounds for some certain order statistics in samples from the (Gomp(α, β)) distribution has been studied in the presence of outlier arising from different members of the same family of distributions. By using a bivariate prior density for α and β a single outlier of types β β0 and β + β0 are obtained. Markov Chain Monte carlo (MCMC) has been used to obtain Bayesian prediction intervals for both single outliers of types β β0 and β + β0. Numerical examples are used to illustrate the procedure.
 

Research Date
Research Department
Research Journal
Journal of Applied Probability and Statistics
Research Member
Research Publisher
ISOSS Publisher
Research Rank
1
Research Vol
17
Research Year
2022
Research Pages
15-31