E-ISSN 3043-6125 | ISSN 3043-6133
 

Research Article 


Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets

Sule Omeiza Bashiru, Alhaji Modu Isa, Ibrahim Ali.


Abstract
This study presents the cosine Gompertz (COG) distribution, which is developed by integrating the cosine generator with the traditional Gompertz distribution. The research explores various statistical characteristics of the COG distribution, and the model parameters are estimated using the maximum likelihood estimation method. It is shown that the hazard rate function of the COG distribution increases monotonically. The probability density function (PDF) of the COG distribution exhibits a range of shapes, including increasing-decreasing, approximately symmetric, and right-skewed patterns. Monte Carlo simulations demonstrate that the estimators for the COG model are consistent, as evidenced by the observed reduction in absolute bias and root mean square error with increasing sample sizes, indicating improved accuracy of the estimators as the number of observations grows. The COG distribution is tested on two real-life datasets and compared with other existing lifetime distributions. The findings suggest that the COG distribution offers a superior fit to both datasets compared to the alternative distributions.

Key words: Cosine G, Gompertz Distribution, Quantile Function, Moment, Maximum Likelihood Estimation


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Sule Omeiza Bashiru
Articles by Alhaji Modu Isa
Articles by Ibrahim Ali
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

Bashiru SO, Isa AM, Ali I. Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets. CUJOSTECH. 2024; 1(2): 42-52. doi:10.5455/CUJOSTECH.241013


Web Style

Bashiru SO, Isa AM, Ali I. Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets. https://www.cujostech.com.ng/?mno=217671 [Access: February 24, 2025]. doi:10.5455/CUJOSTECH.241013


AMA (American Medical Association) Style

Bashiru SO, Isa AM, Ali I. Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets. CUJOSTECH. 2024; 1(2): 42-52. doi:10.5455/CUJOSTECH.241013



Vancouver/ICMJE Style

Bashiru SO, Isa AM, Ali I. Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets. CUJOSTECH. (2024), [cited February 24, 2025]; 1(2): 42-52. doi:10.5455/CUJOSTECH.241013



Harvard Style

Bashiru, S. O., Isa, . A. M. & Ali, . I. (2024) Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets. CUJOSTECH, 1 (2), 42-52. doi:10.5455/CUJOSTECH.241013



Turabian Style

Bashiru, Sule Omeiza, Alhaji Modu Isa, and Ibrahim Ali. 2024. Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets. Confluence University Journal of Science and Technology, 1 (2), 42-52. doi:10.5455/CUJOSTECH.241013



Chicago Style

Bashiru, Sule Omeiza, Alhaji Modu Isa, and Ibrahim Ali. "Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets." Confluence University Journal of Science and Technology 1 (2024), 42-52. doi:10.5455/CUJOSTECH.241013



MLA (The Modern Language Association) Style

Bashiru, Sule Omeiza, Alhaji Modu Isa, and Ibrahim Ali. "Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets." Confluence University Journal of Science and Technology 1.2 (2024), 42-52. Print. doi:10.5455/CUJOSTECH.241013



APA (American Psychological Association) Style

Bashiru, S. O., Isa, . A. M. & Ali, . I. (2024) Cosine Gompertz Distribution: Properties, Simulation and Application to Covid-19 and Reliability Engineering Datasets. Confluence University Journal of Science and Technology, 1 (2), 42-52. doi:10.5455/CUJOSTECH.241013