The extended gamma distribution with regression model and applications

被引:10
作者
Altun, Emrah [1 ]
Korkmaz, Mustafa C. [2 ]
El-Morshedy, M. [3 ,4 ]
Eliwa, M. S. [4 ]
机构
[1] Bartin Univ, Dept Math, Bartin, Turkey
[2] Artvin Coruh Univ, Dept Measurement & Evaluat, Artvin, Turkey
[3] Prince Sattam bin Abdulaziz Univ, Coll Sci & Humanities, Dept Math, Al Kharj 11942, Saudi Arabia
[4] Mansoura Univ, Fac Sci, Dept Math, Mansoura 35516, Egypt
来源
AIMS MATHEMATICS | 2021年 / 6卷 / 03期
关键词
xgamma distribution; gamma distribution; maximum likelihood; method of moments; bias-correction; randomized quantile residuals; MAXIMUM-LIKELIHOOD ESTIMATORS; LINDLEY DISTRIBUTION; MIXTURE; PARAMETERS;
D O I
10.3934/math.2021147
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Y This paper introduces a new extension of the gamma distribution, named as a new extended gamma distribution, via mixture representation of xgamma and gamma distributions. The statistical properties of the proposed distribution are derived such as moment generating and characteristic functions, variance, skewness, and kurtosis measures, Lorenz curve, and mean residual life function. The maximum likelihood, parametric bootstrap, method of moments, least squares, and weighted least squares estimation methods are considered to obtain the unknown model parameters. The finite sample performance of estimation methods is discussed via a simulation study. Using the proposed distribution, we propose a new regression model for the right-skewed response variable as an alternative to the gamma regression model. Two real data sets are analyzed to convince the readers for the usefulness of the proposed model.
引用
收藏
页码:2418 / 2439
页数:22
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