Minimax estimators for the lower-bounded scale parameter of a location-scale family of distributions

被引:1
|
作者
Tripathi, Yogesh Mani [1 ]
Kumar, Somesh [2 ]
Petropoulos, C. [3 ]
机构
[1] Indian Inst Technol Patna, Dept Math, Bihta, India
[2] Indian Inst Technol, Dept Math, Kharagpur, W Bengal, India
[3] Univ Patras, Dept Math, Rion 26504, Greece
关键词
Generalized Bayes estimator; IERD method; Minimaxity; EXPONENTIAL-DISTRIBUTION; UNKNOWN LOCATION; EQUIVARIANT ESTIMATORS; INADMISSIBILITY; VARIANCE;
D O I
10.1080/03610926.2016.1205611
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
This article is concerned with the minimax estimation of a scale parameter under the quadratic loss function where the family of densities is location-scale type. We obtain results for the case when the scale parameter is bounded below by a known constant. Implications for the estimation of a lower-bounded scale parameter of an exponential distribution are presented under unknown location. Furthermore, classes of improved minimax estimators are derived for the restricted parameter using the Integral Expression for Risk Difference (IERD) approach of Kubokawa (1994). These classes are shown to include some existing estimators from literature.
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页码:9185 / 9193
页数:9
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