Numerical Methods for Statistical Data Generation

Authors

  • Hayder Abdulabbas Hasan ministry of education, Baghdad, Iraq

DOI:

https://doi.org/10.29304/jqcsm.2024.16.21550

Keywords:

Monte Carlo Simulation, Numerical Methods, Root Finding

Abstract

A comprehensive comparison was undertaken between two numerical methods, namely bisection and secant methods, to generate random variable data for distribution. two methodologies were suggested to acquire the initial guesses for secant and interval for the bisection method. The results of 100 cases for the choices of the parameters are shown and a comparison was made according to the number of iterations between the methods that was conducted.

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References

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Published

2024-06-30

How to Cite

Abdulabbas Hasan, H. (2024). Numerical Methods for Statistical Data Generation. Journal of Al-Qadisiyah for Computer Science and Mathematics, 16(2), Math. 29–35. https://doi.org/10.29304/jqcsm.2024.16.21550

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Section

Math Articles