Robust location and scale estimation based on the univariate generalized t (GT) distribution

被引:15
作者
Arslan, O [1 ]
Genç, AI [1 ]
机构
[1] Cukurova Univ, Fac Arts & Sci, Dept Math, TR-01330 Adana, Turkey
关键词
univariate GT distribution; Box and Tiao (BT) distribution; generalized gamma (GG) distribution; maximum likelihood estimation; M-estimation; robustness; influence function;
D O I
10.1081/STA-120022242
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];
摘要
In this paper, we consider the univariate generalized I (GT) distribution, which is introduced by McDonald and Newey ((1988) Partially adaptive estimation of regression models via the generalized t distribution. Econometric Theory 4:428-457.). We show that the maximum likelihood estimators for the location and the scale parameters of a GT distribution with known shape parameters can provide alternative robust estimators for the location and scale parameters of a data set. We investigate the existence and the uniqueness of the maximum likelihood estimators. We show that the likelihood function can be unimodal or multimodal depending on the different choices of the shape parameters.
引用
收藏
页码:1505 / 1525
页数:21
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