Generalized order statistics: an exponential family in model parameters

被引：23

作者：

Bedbur, Stefan ^{[1
]}

Beutner, Eric ^{[2
]}

Kamps, Udo ^{[1
]}

机构：

[1] Rhein Westfal TH Aachen, Inst Stat, D-52056 Aachen, Germany

[2] Maastricht Univ, Dept Quantitat Econ, NL-6200 MD Maastricht, Netherlands

来源：

STATISTICS | 2012年 / 46卷 / 02期

关键词：

sequential order statistics; conditional proportional hazard rates; sequential k-out-of-n system; regular exponential family; maximum likelihood estimation; uniformly minimum variance unbiased estimation; Fisher information matrix; asymptotic efficiency; DISTRIBUTIONS; INFERENCE;

D O I：

10.1080/02331888.2010.498046

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：

Generalized order statistics, and thus sequential order statistics with conditional proportional hazard rates, are shown to form a regular exponential family in the model parameters. This structure is utilized to derive maximum likelihood estimators for these parameters or functions of them along with several properties of the estimators. The Fisher information matrix is stated, and asymptotic efficiency is shown.

引用

页码：159 / 166

页数：8

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