Title : ( Bayesian prediction ofk-record values based on progressively censored data from exponential distribution )
Authors: Jafar Ahmadi , Seyed Mohammad Taghi Kamel Mirmostafaee , N. Balakrishnan ,
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Abstract
In this paper, based on a progressively Type-II right censored sample, we discuss the prediction of k-record values from a future sequence. By considering the parent distribution as exponential, we derive Bayesian prediction intervals as well as Bayesian point predictors for k-record values from a future sequence based on an observed progressively Type-II right censored sample. The corresponding results for ordinary Type-II censored sample and the usual order statistics are then deduced as special cases. A real data concerning the breakdown times of an insulating fluid in an accelerated life-test are used for illustrating all the results developed here.
Keywords
, highest posterior density; interval prediction; point prediction; predictive density; progressive Type, II right censoring; record values; k, records
@article{paperid:1018966,
author = {Ahmadi, Jafar and Kamel Mirmostafaee, Seyed Mohammad Taghi and N. Balakrishnan},
title = {Bayesian prediction ofk-record values based on progressively censored data from exponential distribution},
journal = {Journal of Statistical Computation and Simulation},
year = {2012},
volume = {82},
number = {1},
month = {January},
issn = {0094-9655},
pages = {51--62},
numpages = {11},
keywords = {highest posterior density; interval prediction; point prediction; predictive density; progressive
Type-II right censoring; record values; k-records},
}
%0 Journal Article
%T Bayesian prediction ofk-record values based on progressively censored data from exponential distribution
%A Ahmadi, Jafar
%A Kamel Mirmostafaee, Seyed Mohammad Taghi
%A N. Balakrishnan
%J Journal of Statistical Computation and Simulation
%@ 0094-9655
%D 2012
