A novel optimization algorithm for estimating the parameters of the truncated distribution depending on survival function | [Pakistan Journal of Statistics • 2024]

Author(s):

1. Noor Abdul Ameer Jabbar: Department of Mathematics College of Education for Pure Sciences (Ibn Al-Haitham) University of Baghdad,,Iraq

2. Bayda Atiya Kalaf: Department of Mathematics College of Education for Pure Sciences (Ibn Al-Haitham) University of Baghdad,,Iraq

Abstract:

This paper introduces Right Truncated Inverse Generalized Rayleigh distribution (RTIGRD) with two parameters ? and ? with some of its properties as; (Survival-Function, Probability Density Function, Hazard-Function, Cumulative Distribution Function, R-Th Moment, Mean, Variance, Median, Moment Generating Function, and Mode. In addition, we propose a new hybrid algorithm (Artificial Bee Colony Algorithm with Firefly Algorithm (ABC_FA)) to estimate Survival functions based on the parameters (?, ?)of (RTIGRD). Simulation is utilized to compare the proposed algorithm with traditional methods (Maximum Likelihood Estimator and moment method) and standard algorithms (Artificial Bee Colony Algorithm and Firefly Algorithm). The results show proposed approach (ABC_FA) provides a 100% accurate estimate of the survival function for the cases selected in this research, as it has a less mean square error than other estimation methods.

Page(s): 105-122

DOI: DOI not available

Published: Journal: Pakistan Journal of Statistics, Volume: 40, Issue: 1, Year: 2024

Keywords:

Hybrid algorithm , maximum likelihood estimation method , Firefly Algorithm , moment method , Bee Colony Algorithm , Right Truncated Inverse Generalized Rayleigh distribution

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