The exponential generalized log-logistic model: Bagdonavicius-Nikulin test for validation and non-Bayesian estimation methods

被引：0
|
作者：
Ibrahim, Mohamed [1 ]
Aidi, Khaoula [2 ]
Ali, Mir Masoom [3 ]
Yousof, Haitham M. [4 ]
机构：
[1] Damietta Univ, Dept Appl Math & Actuarial Stat, Kafr Saad, Damietta Govern, Egypt
[2] Univ Badji Mokhtar, Lab Probabil & Stat LaPS, Annaba, Algeria
[3] Ball State Univ, Dept Math Sci, Muncie, IN 47306 USA
[4] Benha Univ, Dept Stat Math & Insurance, Banha, Egypt
来源：
COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS | 2022年 / 29卷 / 01期
关键词：
Bagdonavicius-Nikulin test; Barzilai-Borwein; Anderson Darling estimation; log-logistic model; Cramer-von-Mises estimation; OF-FIT TEST; DISTRIBUTIONS; BURR;
D O I：
10.29220/CSAM.2022.29.1.001
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：
A modified Bagdonavicius-Nikulin chi-square goodness-of-fit is defined and studied. The lymphoma data is analyzed using the modified goodness-of-fit test statistic. Different non-Bayesian estimation methods under complete samples schemes are considered, discussed and compared such as the maximum likelihood least square estimation method, the Cramer-von Mises estimation method, the weighted least square estimation method, the left tail-Anderson Darling estimation method and the right tail Anderson Darling estimation method. Numerical simulation studies are performed for comparing these estimation methods. The potentiality of the new model is illustrated using three real data sets and compared with many other well-known generalizations.
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页码：1 / 25
页数：25
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