Main Article Content

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 COVID-19 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.

Keywords

Discretization type II half logistics exponential maximum likelihood estimation Simulation study COVID-19

Article Details

How to Cite
Muhammad Ahsan ul Haq, Babar, A., Hashmi, S., Alghamdi, A. S., & Afify, A. Z. (2021). The Discrete Type-II Half-Logistic Exponential Distribution with Applications to COVID-19 Data . Pakistan Journal of Statistics and Operation Research, 17(4), 921-932. https://doi.org/10.18187/pjsor.v17i4.3772

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