Optimal prediction-intervals for the exponential distribution, based on generalized order statistics

This paper proposes optimal prediction intervals for the future generalized order statistic (GOS) based on the first r GOS (ordinary order statistics, usual record values, k-record values) from an exponential population. A conditional argument is considered for obtaining an optimal prediction interv...

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Bibliographic Details
Published in:	IEEE transactions on reliability Vol. 50; no. 1; pp. 112 - 115
Main Author:	Zayed Raqab, M.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01-03-2001 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Distribution functions Electric shock Error analysis Exponential distribution Intervals Maximum likelihood estimation Optimization Predictive models Probability density function Random variables Statistical distributions Statistics Voltage
Online Access:	Get full text
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Summary:	This paper proposes optimal prediction intervals for the future generalized order statistic (GOS) based on the first r GOS (ordinary order statistics, usual record values, k-record values) from an exponential population. A conditional argument is considered for obtaining an optimal prediction interval for future GOS. A numerical example illustrates this technique.
Bibliography:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23
ISSN:	0018-9529 1558-1721
DOI:	10.1109/24.935025