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Bayesian Prediction Regions for the Extreme Order Statistics
Author(s) -
Lingappaiah G. S.
Publication year - 1984
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710260109
Subject(s) - statistics , order statistic , mathematics , bayesian probability , bayesian statistics , series (stratigraphy) , summary statistics , set (abstract data type) , econometrics , bayesian inference , computer science , paleontology , biology , programming language
In this paper, prediction bounds for the order statistics are dealt with. For this purpose, predictive distributions derived by Bayesian approach, are utilized. In particular, bounds for the smallest and the largest order statistics are set when a series of samples are drawn from exponential, Pareto and power function populations. These bounds assist in knowing the nature of these predicted statistics even without actually having the sample observations.