Comparing the Cuckoo Algorithm with Other Algorithms for Estimating Two GLSD Parameters


Jane Jaleel Stephan, Haitham Sabah Hasan and Alaa Hamza Omran, 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.


Cuckoo search optimization (CSO) algorithm, maximum likelihood estimation (MLE) algorithm, method of moments (MOM) algorithm, mean square error (MSE).

Full Text  Volume 7, Number 10