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

Authors

  • Salam Jasim Mohammed
  • Ali Khalid Khudair
  • Shurooq kadhum shaffeq

DOI:

https://doi.org/10.33095/jeas.v28i132.2281

Keywords:

Genetic algorithm, Gumbel Distribution, likelihood Function , loss Function, الخوارزمية الجينية, توزيع كامبل , الامكان الاعظم, دالة الخسارة

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).

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Published

2022-06-30

How to Cite

Jasim Mohammed, S. ., Khalid Khudair, A. . . and kadhum shaffeq , S. . (2022) “Using Genetic Algorithm to Estimate the Parameters of the Gumbel Distribution Function by Simulation”, Journal of Economics and Administrative Sciences, 28(132), pp. 146–156. doi: 10.33095/jeas.v28i132.2281.

Issue

Section

Statistical Researches