The Discrete Type-II Half-Logistic Exponential Distribution with Applications to COVID-19 Data | [Pakistan Journal of Statistics and Operation Research • 2021]

Author(s):

1. Muhammad Ahsan-ul-Haq: College of Statistical & Actuarial Sciences, University of the Punjab, Pakistan

2. Ayesha Babar: School of Statistics, Minhaj University Lahore, Pakistan

3. Sharqa Hashmi: Department of Statistics, Lahore College for Women University, Lahore, Pakistan

4. Abdulaziz S. Alghamdi: Department of Mathematics, College of Science & Arts, King Abdulaziz University, P.O. Box 344, Rabigh 21911, Saudi Arabia

5. Ahmed Z. Afify: Department of Statistics, Mathematics and Insurance, Benha University,Benha 13511, Egypt

Abstract:

We propose a new two-parameter discrete model, called discrete Type-II half-logistics exponential (DTIIHLE) distribution using the survival discretization approach. The DTIIHLE distribution can be utilized to model COVID19 data. The model parameters are estimated using the maximum likelihood method. A simulation study is conducted to evaluate the performance of the maximum likelihood estimators. The usefulness of the proposed distribution is evaluated using two real-life COVID-19 data sets. The DTIIHLE distribution provides a superior fit to COVID-19 data as compared with competitive discrete models including the discrete-Pareto, discrete Burr-XII, discrete log-logistic, discrete-Lindley, discrete-Rayleigh, discrete inverse-Rayleigh, and natural discrete-Lindley.

Page(s): 921-932

DOI: 10.18187/pjsor.v17i4.3772

Published: Journal: Pakistan Journal of Statistics and Operation Research, Volume: 17, Issue: 4, Year: 2021

Keywords:

maximum likelihood estimation , simulations , Discretization , COVID19 data , type II half logistics exponential

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