10.57647/ijm2c.2026.1604.25

Monte Carlo Performance Evaluation of Maximum Likelihood Estimators for the Bivariate Exponentiated Generalized Weibull-Gompertz Power Series (BEGWGPS) Distribution

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  • Kianoush Fathi Vajargah*1,
  • Elham Masharpour1,
  • Parvin Azhdari1,
  1. Department of Statistics, NT.C., Islamic Azad University, Tehran, Iran

Received: 16-02-2026

Revised: 08-05-2026

Accepted: 15-05-2026

Published in Issue 21-05-2026

Copyright (c) 2025 Kianoush Fathi Vajargah, Elham Masharpour, Parvin Azhdari (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Fathi Vajargah, K., Masharpour, E., & Azhdari, P. (2026). Monte Carlo Performance Evaluation of Maximum Likelihood Estimators for the Bivariate Exponentiated Generalized Weibull-Gompertz Power Series (BEGWGPS) Distribution. International Journal of Mathematical Modelling & Computations. https://doi.org/10.57647/ijm2c.2026.1604.25
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Abstract

Simulations affects our life every day through our interactions and the use of various simulation method has become widespread in elds of science. Among the various simulation, the monte carlo simulation is type of simulation that relies on repeated random sampling and statistical analysis to compute the result. This article attempts to introduce this method for simulating New Bivariate Generalized Exponential Weibull Gomperts Power Series parameters in order to show the flexibility and potentiality of the new class of distribution.

 

Keywords

  • Generalized Exponential Power Series Distributions,
  • Generalized Exponential Weibull Gomperts Power Series Distributions,
  • Monte Carlo Simulation,
  • Maximum likelihood estimation
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References

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