- Necmettin Erbakan Üniversitesi Fen ve Mühendislik Bilimleri Dergisi
- Cilt: 5 Sayı: 2
- Maximum Likelihood Estimation for the Nakagami Distribution Using Particle Swarm Optimization Algori...
Maximum Likelihood Estimation for the Nakagami Distribution Using Particle Swarm Optimization Algorithm with Applications
Authors : Adi Omaia Faouri, Pelin Kasap
Pages : 209-218
Doi:10.47112/neufmbd.2023.19
View : 53 | Download : 61
Publication Date : 2023-12-31
Article Type : Research
Abstract :The Nakagami distribution originated to model the fading of radio signals and is widely used in various disciplines. In this study, the maximum likelihood (ML) estimation method is used to estimate the shape and scale parameters of the distribution. However, there are no explicit solutions to the likelihood equations for this distribution. Therefore, three main algorithms, the particle swarm optimization algorithm (PSO), the genetic algorithm (GA), and the quasi-newton (QN) algorithm, have been used to solve these equations. Comparisons of the performances of these algorithms have been made with a comprehensive Monte-Carlo simulation study, taking into account the bias, mean squared error (MSE), and deficiency (DEF) criteria. The model has been applied to four real data sets in order to demonstrate its usefulness.Keywords : En çok olabilirlik, Nakagami dağılımı, Parçacık sürü optimizasyon