Bayesian Prediction Bounds, Ordered Ranked Set Sampling

What is it about?

In this article, inference for the modified Weibull distribution under type-II doubly censored sample is discussed. Maximum likelihood estimator and Bayes estimators based on conjugate and discrete priors are derived for three unknown parameters. The BEs are studied under squared error loss and LINEX error loss functions. The Bayesian prediction of the ℓ-th ordered observation in a sample of size n from MW distribution is obtained. A real life data set and simulation data are used to illustrate the results derived.

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Why is it important?

we have considered the problem of prediction of unobserved items from modified Weibull distribution based on doubly type-II censored data when all the parameters are unknown. For this, we tackle the problem by obtaining point BP and another ABP of the ℓth failure time as well as PIs of the unobserved items. Further, BEs under both symmetric and asymmetric loss functions are also obtained. Our findings in this article are applied and illustrated by using real life and simulated data sets.

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