Linear Estimators and Predictors Based on Generalized Order Statistics from Generalized Pareto Distributions

被引：22

作者：

Burkschat, M. ^{[1
]}

机构：

[1] Otto Von Guericke Univ, Inst Stat Math, D-39016 Magdeburg, Germany

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2010年 / 39卷 / 02期

关键词：

BLUE; best linear unbiased estimator; BLEE; Best linear invariant estimator; BLIE; Non-Negativity of BLUE; Best linear unbiased predictor; BLUP; Best linear invariant predictor; Exponential distribution; Location and scale parameters; Pareto distribution; Uniform distribution; UNBIASED PREDICTION; LOCATION; PARAMETER;

D O I：

10.1080/03610920902746630

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：

Linear estimation and prediction based on several samples of generalized order statistics from generalized Pareto distributions is considered. Representations of best linear unbiased estimators (BLUEs) and best linear equivariant estimators in location-scale families are derived, as well as corresponding optimal linear predictors. Moreover, we study positivity of the linear estimators of the scale parameter. An example illustrates that the BLUE may attain negative values with positive probability in certain situations.

引用

页码：311 / 326

页数：16

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