Gerçek Veri Uygulamaları ile Log Exponential-Power Dağılımı için Parametre Tahmin Prosedürleri

Year 2022, Volume: 12 Issue: 2, 193 - 202, 30.12.2022

Mustafa Ç. KORKMAZ Kadir KARAKAYA Yunus AKDOĞAN

https://doi.org/10.37094/adyujsci.1073616

Abstract

Bu makalede, log exponential-power dağılımının iki parametresini tahmin etmek için çeşitli tahmin yöntemleri araştırılmıştır. En çok olabilirlik, kuantil, en küçük kareler, ağırlıklandırılmış en küçük kareler, Anderson-Darling ve Cramer-von Mises tahmin yöntemleri detaylı olarak incelenmiştir. Bu tahmin edicilerin performanslarını değerlendirmek için Monte Carlo simülasyon deneyleri yapılmıştır. Ayrıca dört gerçek veri uygulaması gerçekleştirilmiş ve tüm tahmin ediciler Kolmogorov-Smirnov istatistiği sonuçları sunulmuştur.

Keywords

Nokta tahmini, Log exponential-power dağılımı, En çok olabilirlik tahmini, Gerçek veri uygulaması

Parameter Estimation Procedures for Log Exponential-Power Distribution with Real Data Applications

Abstract

In this study, some estimation techniques are investigated to estimate two parameters of the log exponential-power distribution. The maximum likelihood, quantile, least squares, weighted least squares, Anderson-Darling, and Cramer-von Mises estimation methods are studied in detail. The efficiency of these estimators is validated through Monte Carlo simulation experiments. Also, four real data applications are performed and Kolmogorov-Smirnov statistic results for all estimators are presented.

Keywords

Point estimation, Log exponential-power distribution, Maximum likelihood estimators, Practical data application, Nokta tahmini, Log exponential-power dağılımı, En çok olabilirlik tahmini, Gerçek veri uygulaması.

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