Application of Odd Chen-Log-Logistic Distribution to Covid-19 Data
Year: 2024
Type: article
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.
Institution: University of Tirana
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404185341