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Using Cuckoo Algorithm for Estimating Two GLSD Parameters and Comparing it With Other Algorithms


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1 University of Information Technology & Communications, Iraq
 

This study introduces and compares different methods for estimating the two parameters of generalized logarithmic series distribution. These methods are the cuckoo search optimization, maximum likelihood estimation, and method of moments algorithms. All the required derivations and basic steps of each algorithm are explained. The applications for these algorithms are implemented through simulations using different sample sizes (n = 15, 25, 50, 100). Results are compared using the statistical measure mean square error.

Keywords

Cuckoo Search Optimization (CSO) Algorithm, Maximum Likelihood Estimation (MLE) Algorithm, Method of Moments (MOM) Algorithm, Mean Square Error (MSE).
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  • Using Cuckoo Algorithm for Estimating Two GLSD Parameters and Comparing it With Other Algorithms

Abstract Views: 315  |  PDF Views: 149

Authors

Jane Jaleel Stephan
University of Information Technology & Communications, Iraq
Haitham Sabah Hasan
University of Information Technology & Communications, Iraq
Alaa Hamza Omran
University of Information Technology & Communications, Iraq

Abstract


This study introduces and compares different methods for estimating the two parameters of generalized logarithmic series distribution. These methods are the cuckoo search optimization, maximum likelihood estimation, and method of moments algorithms. All the required derivations and basic steps of each algorithm are explained. The applications for these algorithms are implemented through simulations using different sample sizes (n = 15, 25, 50, 100). Results are compared using the statistical measure mean square error.

Keywords


Cuckoo Search Optimization (CSO) Algorithm, Maximum Likelihood Estimation (MLE) Algorithm, Method of Moments (MOM) Algorithm, Mean Square Error (MSE).

References