A Lecturer from the Department of Mathematics Publishes a Global Research Paper.
Asst. Prof. Dr. Hazem Ghadeeb Kalt from the Department of Mathematics published a research paper titled “New technique to estimate the parameters for extended exponential distribution”
A new technique for estimating the parameters of the extended exponential distribution.
It was published in the journal “3rd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA)” published by IEEE Scopus.
The aim of this research was to propose a new modified technique for verifying the estimation of two parameters associated with the extended exponential distribution.
Abstract: In this paper, a new modified technique was proposed for verifying the estimation of two parameters associated with the extended exponential distribution.
The research included adopting the new method (the modified multiple regression least squares estimator) with two other methodologies that use comprehensive datasets, specifically the method known as maximum likelihood estimation (MLE) and the method of moments (ME).
The study has come up with the derivation of these methods and the calculation of a general mathematical formula for each parameter. These three methods were compared through Monte Carlo simulation and using the mean square error (MSE) criterion on multiple samples with different sizes and values for varying parameters. The comparative analysis conducted in this research indicates that the modified multiple regression least squares estimator methodology outperforms alternative methods.
