Maximum Likelihood Estimation for the Inverted Kumaraswamy Distribution Based on the Extreme Ranked Set Sampling

Esra Demirel; Hasan Hüseyin Gül

Makale detayları

Maximum Likelihood Estimation for the Inverted Kumaraswamy Distribution Based on the Extreme Ranked Set Sampling

Yazarlar:

Esra Demirel | Hasan Hüseyin Gül

Yayıncı:

Bitlis Eren University

Ana Başlıklar:

Probability Theory | Theory of Sampling | Applied Statistics

Dergi:

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi Vol.14 Issue 2, pp.952-970

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001351283

pISSN:

2147-3129

Anahtar kelimeler:

Özet:

 This study investigates the use of extreme ranked set sampling ERSS for parameter estimation in the Inverted Kumaraswamy IK distribution. The Kumaraswamy distribution has wide applications in fields such as reliability testing, environmental studies, financial analysis, and survival analysis. The paper emphasizes the efficiency advantages of ERSS, particularly in capturing extreme values, which are crucial for distributions with heavy tails or skewed data. By incorporating ERSS, this research demonstrates that more accurate and efficient parameter estimates can be obtained compared to traditional sampling methods like simple random sampling SRS. A simulation study is also performed to demonstrate the performance of the proposed estimators. Finally, a real data set is presented for illustrative purposes. The findings suggest that ERSS outperforms SRS in terms of precision, particularly in contexts where extreme values play a significant role. This work contributes to the advancement of sampling techniques for extreme value contexts, with potential applications in various fields, including environmental research, finance, and reliability analysis.

 This study investigates the use of extreme ranked set sampling ERSS for parameter estimation in the Inverted Kumaraswamy IK distribution. The Kumaraswamy distribution has wide applications in fields such as reliability testing, environmental studies, financial analysis, and survival analysis. The paper emphasizes the efficiency advantages of ERSS, particularly in capturing extreme values, which are crucial for distributions with heavy tails or skewed data. By incorporating ERSS, this research demonstrates that more accurate and efficient parameter estimates can be obtained compared to traditional sampling methods like simple random sampling SRS. A simulation study is also performed to demonstrate the performance of the proposed estimators. Finally, a real data set is presented for illustrative purposes. The findings suggest that ERSS outperforms SRS in terms of precision, particularly in contexts where extreme values play a significant role. This work contributes to the advancement of sampling techniques for extreme value contexts, with potential applications in various fields, including environmental research, finance, and reliability analysis.

 This study investigates the use of extreme ranked set sampling ERSS for parameter estimation in the Inverted Kumaraswamy IK distribution. The Kumaraswamy distribution has wide applications in fields such as reliability testing, environmental studies, financial analysis, and survival analysis. The paper emphasizes the efficiency advantages of ERSS, particularly in capturing extreme values, which are crucial for distributions with heavy tails or skewed data. By incorporating ERSS, this research demonstrates that more accurate and efficient parameter estimates can be obtained compared to traditional sampling methods like simple random sampling SRS. A simulation study is also performed to demonstrate the performance of the proposed estimators. Finally, a real data set is presented for illustrative purposes. The findings suggest that ERSS outperforms SRS in terms of precision, particularly in contexts where extreme values play a significant role. This work contributes to the advancement of sampling techniques for extreme value contexts, with potential applications in various fields, including environmental research, finance, and reliability analysis.

 This study investigates the use of extreme ranked set sampling ERSS for parameter estimation in the Inverted Kumaraswamy IK distribution. The Kumaraswamy distribution has wide applications in fields such as reliability testing, environmental studies, financial analysis, and survival analysis. The paper emphasizes the efficiency advantages of ERSS, particularly in capturing extreme values, which are crucial for distributions with heavy tails or skewed data. By incorporating ERSS, this research demonstrates that more accurate and efficient parameter estimates can be obtained compared to traditional sampling methods like simple random sampling SRS. A simulation study is also performed to demonstrate the performance of the proposed estimators. Finally, a real data set is presented for illustrative purposes. The findings suggest that ERSS outperforms SRS in terms of precision, particularly in contexts where extreme values play a significant role. This work contributes to the advancement of sampling techniques for extreme value contexts, with potential applications in various fields, including environmental research, finance, and reliability analysis.

Makale detayları

Maximum Likelihood Estimation for the Inverted Kumaraswamy Distribution Based on the Extreme Ranked Set Sampling

Yazarlar:

Esra Demirel | Hasan Hüseyin Gül

Yayıncı:

Bitlis Eren University

Ana Başlıklar:

Probability Theory | Theory of Sampling | Applied Statistics

Dergi:

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi Vol.14 Issue 2, pp.952-970

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001351283

pISSN:

2147-3129

Inverted Kumaraswamy Distribution

Ranked Set Sampling

Extreme Ranked Set Sampling

Maximum Likelihood Estimator

Sayı

Makale detayları

Maximum Likelihood Estimation for the Inverted Kumaraswamy Distribution Based on the Extreme Ranked Set Sampling

Yazarlar: Esra Demirel | Hasan Hüseyin Gül

Yayıncı: Bitlis Eren University

Ana Başlıklar: Probability Theory | Theory of Sampling | Applied Statistics

Dergi: Bitlis Eren Üniversitesi Fen Bilimleri Dergisi Vol.14 Issue 2, pp.952-970

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001351283

pISSN: 2147-3129

Inverted Kumaraswamy Distribution

Ranked Set Sampling

Extreme Ranked Set Sampling

Maximum Likelihood Estimator

Sayı

Yazarlar:

Esra Demirel | Hasan Hüseyin Gül

Yayıncı:

Bitlis Eren University

Ana Başlıklar:

Probability Theory | Theory of Sampling | Applied Statistics

Dergi:

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi Vol.14 Issue 2, pp.952-970

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001351283

pISSN:

2147-3129