WSEAS Transactions on Mathematics
Print ISSN: 1109-2769, E-ISSN: 2224-2880
Volume 23, 2024
Application of Odd Chen-Log-Logistic Distribution to Covid-19 Data
Authors: , , ,
Abstract: This article created the Odd Chen-Log-Logistic distribution from Odd Chen-G family distributions. We derive various statistical features. The parameter estimation theory focuses on selecting the best estimators. We estimate distribution parameters using maximum likelihood, moment, least squares, weighted least, L-moment, maximum product spacing, and minimal distance methods. We will examine Kolmogorov-Smirnov simulation studies that compare estimator efficiency. Finally, we analyze a genuine COVID-19 data set to demonstrate the flexibility of our model and its accuracy compared to other distributions.