Using Genetic Algorithm to Estimate the Parameters of the Gumbel Distribution Function by Simulation

Authors

• Salam Jasim Mohammed, Al-Karkh University of Science, Baghdad, Iraq
• Ali Khalid Khudair, Al-Karkh University of Science, Baghdad, Iraq
• Shurooq kadhum Shaffeq, Al-Karkh University of Science, Baghdad, Iraq

Abstract

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as the Bayes method. The comparison was made using the mean error squares (MSE), where the best estimator is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

DOI

10.33095/jeas.v28i132.2281

Subject Area

Statistical

First Page

146

Last Page

156

Rights

http://creativecommons.org/licenses/by-nc-nd/4.0

Recommended Citation

Mohammed, S. J., Khudair, A. K., & Shaffeq, S. k. (2022). Using Genetic Algorithm to Estimate the Parameters of the Gumbel Distribution Function by Simulation. Journal of Economics and Administrative Sciences, 28(132), 146-156. https://doi.org/10.33095/jeas.v28i132.2281