Exponentiated Reduced Kies Dağılımının Parametreleri için Tahmin Yöntemlerinin Karşılaştırılması

Bu makalede, exponentiated reduced Kies (ERK) dağılımının parametreleri en çok olabilirlik, en küçük kareler, ağırlıklandırılmış en küçük karaler, Cramér-von Mises, Anderson Darling ve sağ-kuyruklu Anderson Darling yöntemleri kullanılarak tahmin edilmiştir. Tahmin edicilerin performansları farklı parametre değerleri ve farklı örneklemler boyutları için Monte-Carlo simülasyon çalışması ile karşılaştırılmıştır. Son olarak, önerilen yöntemlerin uygulanması için gerçek bir veri seti analiz edilmiştir.

Anahtar Kelimeler:

Exponentiated reduced Kies dağılımı, Parametre tahmini, Monte-Carlo simülasyonu, Etkinlik

Comparison of the Estimation Methods for the Parameters of Exponentiated Reduced Kies Distribution

In this paper, we consider the estimation for the parameters of exponentiated reduced Kies (ERK) distribution using maximum likelihood (ML), least squares (LS), weighted least squares (WLS), Cramér-von Mises (CM), Anderson Darling (AD) and right-tail Anderson Darling (RAD) methods. The performances of the estimators are compared via Monte-Carlo simulation study for different parameter settings and different sample sizes. Finally, a real data set is analyzed for the implementation of the proposed methods.

Keywords:

Exponentiated reduced Kies distribution;, Parameter estimation;, Monte-Carlo simulation;, Efficiency,

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