The Exponentiated Generalized Extended Gompertz Distribution

Journal of Data Science

article

Thiago A. N. De Andrade¹  Subrata Chakraborty²  Laba Handique²  Frank Gomes-Silva³ 

[1] Departament of Statistics, Federal University of Pernambuco, Cidade Universit´aria - 50740 − 540;Departament of Statistics, Dibrugarh University;Department of Statistics and Informatics, Federal Rural University of Pernambuco

关键词: Applied results;    exponentiated generalized class;    Gompertz distribution;    probability models with applications;    real data sets;   

DOI  :  10.6339/JDS.201904_17(2).0004

学科分类：土木及结构工程学

来源: JDS

【 摘 要 】

This paper presents a new generalization of the extended Gompertz distribution. We defined the so-called exponentiated generalized extended Gompertz distribution, which has at least three important advantages: (i) Includes the exponential, Gompertz, extended exponential and extended Gompertz distributions as special cases; (ii) adds two parameters to the base distribution, but does not use any complicated functions to that end; and (iii) its hazard function includes inverted bathtub and bathtub shapes, which are particularly important because of its broad applicability in real-life situations. The work derives several mathematical properties for the new model and discusses a maximum likelihood estimation method. For the main formulas related to our model, we present numerical studies that demonstrate the practicality of computational implementation using statistical software. We also present a Monte Carlo simulation study to evaluate the performance of the maximum likelihood estimators for the EGEG model. Three real- world data sets were used for applications in order to illustrate the usefulness of our proposal.

【 授权许可】

CC BY