Pitman Closeness Comparison of Best Linear Unbiased and Invariant Predictors for Exponential Distribution in One- and Two-Sample Situations

被引:12
|
作者
Balakrishnan, N. [2 ]
Davies, Katherine F. [1 ]
Keating, Jerome P. [3 ]
Mason, Robert L. [4 ]
机构
[1] Univ Manitoba, Dept Stat, Winnipeg, MB R3T 2N2, Canada
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON, Canada
[3] Univ Texas San Antonio, Dept Demog, San Antonio, TX USA
[4] SW Res Inst, San Antonio, TX USA
关键词
Best linear invariant estimator; Best linear invariant predictor; Best linear unbiased estimator; Best linear unbiased predictor; Order statistics; Pitman closeness; Probabilities of closeness;
D O I
10.1080/03610920903537301
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Best linear unbiased, best linear invariant, and maximum likelihood predictors are commonly used in reliability studies for predicting either censored failure times or lifetimes from a future life-test. In this article, by assuming a Type-II right-censored sample from an exponential distribution, we compare best linear unbiased (BLUP) and best linear invariant (BLIP) predictors of the censored order statistics in the one-sample case and order statistics from a future sample in the two-sample case, in terms of Pitman closeness criterion. Some specific conclusions are drawn and supporting numerical results are presented.
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页码:1 / 15
页数:15
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