Author(s):
1. Veronica Kariuki:
Department of Mathematics, Pan African Institute of Basic Science Technology and Innovation, Nairobi, Kenya
2. Anthony Wanjoya:
Department of Statistics and Actuarial Sciences Jomo Kenyatta University of Agriculture and Technology Kiambu, Kenya.
3. Oscar Ngesa:
Department of Mathematics, Statistics and Physical Science Taita Taveta University, Voi Kenya.
4. Mohammed Alqawba:
Department of Mathematics, College of Science and Arts Qassim University,Ar Rass,Saudi Arabia
Abstract:
In this paper, we propose a flexible family called the exponentiated alpha-power-G (EAP-G) family. The benefits of the proposed family include its analytical simplicity and its ability to confer flexibility to the baseline distributions in survival analysis. Based on the proposed approach, a three-parameter extension of the exponential distribution called the exponentiated alpha-power exponential (EAPE) distribution is studied in detail. Maximum likelihood is used to estimate the EAPE parameters, and its performance is evaluated via a simulation study. Furthermore, two real-world survival data are used to demonstrate the applicability and examine the flexibility of the proposed distribution. The EAPE distribution is compared to other competing generalizations of the exponential distribution. The real data analysis shows that the proposed model performed better among the competitors and could potentially be very adequate in describing and modeling a wide range of survival data.
Page(s):
237-258
DOI:
DOI not available
Published:
Journal: Pakistan Journal of Statistics, Volume: 39, Issue: 3, Year: 2023
Keywords:
maximum likelihood estimation
,
Simulation study
,
Exponentiated family
,
Exponential distribution
,
alphapower transformation
References:
References are not available for this document.
Citations
Citations are not available for this document.