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Prediction intervals based on Gompertz doubly censored data
Journal article   Peer reviewed

Prediction intervals based on Gompertz doubly censored data

S. F. Niazi Ali
Computational statistics, Vol.31(1), pp.227-246
01/03/2016

Abstract

Mathematics Physical Sciences Science & Technology Statistics & Probability
This article is concerned with the problem of deriving Bayesian prediction bounds for the Gompertz distribution. Based on doubly Type II censored data, Bayesian prediction bounds for both the future observations will be derived. Two different sampling schemes have been considered. A conjugate prior for the one parameter case, as well as a joint prior for the two parameters case are outlined. Some numerical examples are given to illustrate the results.

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