A New Skew-Symmetric Gudermannian-Laplace Distribution with Properties and Application to Wind Speed Data

Abdullah Yılmaz

Makale detayları

A New Skew-Symmetric Gudermannian-Laplace Distribution with Properties and Application to Wind Speed Data

Yazarlar:

Abdullah Yılmaz

Yayıncı:

Osmaniye Korkut Ata Üniversitesi

Ana Başlıklar:

Matematik

Dergi:

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.6 Issue 1, pp.842-853

Belge Tipi:

Makale

Yayın Tarihi:

10/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001284882

pISSN:

2687-3729

Anahtar kelimeler:

Özet:

 We introduce a novel probability distribution that may be used to model both skewed and symmetric data. This new distribution, called the skew-symmetric Gudermanian-Laplace SSGL distribution, includes a shape parameter that allows it to change the asymmetry. Some fundamental statistical properties of the new distribution have been given explicit analytical expressions. The study also includes parameter estimations and simulation sections. We considered two datasets in the real-world data application. The first dataset is the heights of 100 Australian athletes data, which is discussed in many studies examining alternative skewed models. The second dataset contains the average wind speeds recorded by the İstanbul Çatalca meteorological observatory in January 2020. We showed that the SSGL distribution outperforms its well-known alternative, the Skew-Normal distribution, in both datasets. As a result of the study, it was concluded that the SSGL distribution is a suitable alternative for modeling skewed data.

 We introduce a novel probability distribution that may be used to model both skewed and symmetric data. This new distribution, called the skew-symmetric Gudermanian-Laplace SSGL distribution, includes a shape parameter that allows it to change the asymmetry. Some fundamental statistical properties of the new distribution have been given explicit analytical expressions. The study also includes parameter estimations and simulation sections. We considered two datasets in the real-world data application. The first dataset is the heights of 100 Australian athletes data, which is discussed in many studies examining alternative skewed models. The second dataset contains the average wind speeds recorded by the İstanbul Çatalca meteorological observatory in January 2020. We showed that the SSGL distribution outperforms its well-known alternative, the Skew-Normal distribution, in both datasets. As a result of the study, it was concluded that the SSGL distribution is a suitable alternative for modeling skewed data.

 We introduce a novel probability distribution that may be used to model both skewed and symmetric data. This new distribution, called the skew-symmetric Gudermanian-Laplace SSGL distribution, includes a shape parameter that allows it to change the asymmetry. Some fundamental statistical properties of the new distribution have been given explicit analytical expressions. The study also includes parameter estimations and simulation sections. We considered two datasets in the real-world data application. The first dataset is the heights of 100 Australian athletes data, which is discussed in many studies examining alternative skewed models. The second dataset contains the average wind speeds recorded by the İstanbul Çatalca meteorological observatory in January 2020. We showed that the SSGL distribution outperforms its well-known alternative, the Skew-Normal distribution, in both datasets. As a result of the study, it was concluded that the SSGL distribution is a suitable alternative for modeling skewed data.

 Bu makalede hem çarpık hem de simetrik verileri modellemek için kullanılabilecek yeni bir olasılık dağılımı sunuyoruz. Çarpık simetrik Gudermanian-Laplace SSGL dağılımı olarak adlandırılan bu yeni dağılım, asimetriyi değiştirmesine izin veren bir şekil parametresi içerir. Yeni dağılımın bazı temel istatistiksel özelliklerine açık analitik ifadeler verilmiştir. Çalışma aynı zamanda parametre tahminleri ve simülasyon bölümlerini de içermektedir. Gerçek dünya veri uygulamasında ise iki veri kümesini ele aldık. İlk veri seti, alternatif çarpık olasılık modellerini inceleyen birçok çalışmada el alınan 100 Avustralyalı sporcunun boyları verisidir. İkinci veri seti, İstanbul Çatalca meteoroloji gözlemevi tarafından Ocak 2020de kaydedilen ortalama rüzgar hızlarıdır. SSGL dağılımının, her iki veri setinde de iyi bilinen alternatifi olan Çarpık-Normal dağılımından daha iyi performans gösterdiğini gösterdik. Çalışma sonucunda SSGL dağılımının çarpık verilerin modellenmesi için uygun bir alternatif olduğu sonucuna varılmıştır.

Makale detayları

A New Skew-Symmetric Gudermannian-Laplace Distribution with Properties and Application to Wind Speed Data

Yazarlar:

Abdullah Yılmaz

Yayıncı:

Osmaniye Korkut Ata Üniversitesi

Ana Başlıklar:

Matematik

Dergi:

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.6 Issue 1, pp.842-853

Belge Tipi:

Makale

Yayın Tarihi:

10/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001284882

pISSN:

2687-3729

Skew-symmetric distribution

Skewness

Skew Normal distribution

Gudermanian distribution

Laplace distribution

Çarpık-Simetrik dağılım

Çarpıklık

Çarpık Normal dağılım

Gudermanian dağılımı

Laplace dağılımı

Skew-symmetric distribution

Skewness

Skew Normal distribution

Gudermanian distribution

Laplace distribution

Sayı

Makale detayları

Yazarlar: Abdullah Yılmaz

Yayıncı: Osmaniye Korkut Ata Üniversitesi

Ana Başlıklar: Matematik

Dergi: Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.6 Issue 1, pp.842-853

Belge Tipi: Makale

Yayın Tarihi: 10/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001284882

pISSN: 2687-3729

Sayı

Yazarlar:

Abdullah Yılmaz

Yayıncı:

Osmaniye Korkut Ata Üniversitesi

Ana Başlıklar:

Matematik

Dergi:

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.6 Issue 1, pp.842-853

Belge Tipi:

Makale

Yayın Tarihi:

10/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001284882

pISSN:

2687-3729