Bayesian Prediction for Chris-Jerry Model Using Unified Progressive Hybrid Censored Sample
محورهای موضوعی : Operation Researchهانیه پناهی 1 , Sahar Hosseinikhah Choshaly 2
1 - عضو هیات علمی
2 - Department of Management, Islamic Azad University, Lahijan Branch, Lahijan, Iran
کلید واژه: Bayesian point Prediction, HPD predictive, Chris-Jerry distribution, Unified Progressive Hybrid Censoring.,
چکیده مقاله :
From a real analysis standpoint, modeling hinges on the choice of the most suitable analysis method, whether it be a frequentist or Bayesian approach, to obtain an updated model. Modeling lifetime data with heavy tail has been a problem among many management researchers. Also, predicting unobserved data based on available data is one of the most important challenges in various sciences such as management and engineering. Bayesian predictive point in Chris-Jerry distribution is considered, in this paper. Te observed data is censored using a unified progressive hybrid censoring scheme. For evidence of the effectiveness of the given methodology, an application is explored.
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