Bayesian prediction limits for inverse weibull distribution when observations are mid type II censored

Abstract

In this paper, the problem of prediction is discussed for inverse Weibull distribution. Posterior distribution is obtained using different informative priors when observations are mid type II censored. When the shape parameter of the model is known, prediction interval is obtained using predictive probability density function method. Whereas, when both parameters are known, inferences from the posterior distribution are drawn using Bayes computation. Comparisons have been made on the basis of simulated data set for the smallest ordered future observation. © 2021 NSP Natural Sciences Publishing Cor.