Comparison Of Maximum Likelihood And Bayes Estimators Under Symmetric And Asymmetric Loss Functions By Means Of Tierney Kadane’s Approximation  For Weibull Distribution

Gülcan GENCER; Kerem GENCER

Makale detayları

Comparison Of Maximum Likelihood And Bayes Estimators Under Symmetric And Asymmetric Loss Functions By Means Of Tierney Kadane’s Approximation For Weibull Distribution

Yazarlar:

Gülcan GENCER | Kerem GENCER

Yayıncı:

Fırat University

Ana Başlıklar:

Doğal Bilimler

Dergi:

Turkish Journal of Science and Technology 2019 Vol.14 Issue 2, pp.69-78

Belge Tipi:

Makale

Yayın Tarihi:

9/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000639197

Sıklık:

Aylık

eISSN:

1308-9099

pISSN:

1308-9080

Özet:

 





In this study, it is considered the problem
of comparing the performances of the Maximum Likelihood (ML) and Bayes
estimators under symmetric and asymmetric loss function  for the unknown parameters of Weibull
distribution. ML estimators are computed by using the Newton Raphson method. Bayesian
estimations under Squared, Linex and General Entropy loss functions by using
Jeffrey’s extension prior are introduced with Tierney Kadane approximation for
Weibull distribution. For different sample sizes, estimators are compared to
obtain the best estimator in terms of mean squared errors using a Monte Carlo
simulation study.





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Makale detayları

Comparison Of Maximum Likelihood And Bayes Estimators Under Symmetric And Asymmetric Loss Functions By Means Of Tierney Kadane’s Approximation For Weibull Distribution

Yazarlar: Gülcan GENCER | Kerem GENCER

Yayıncı: Fırat University

Ana Başlıklar: Doğal Bilimler

Dergi: Turkish Journal of Science and Technology 2019 Vol.14 Issue 2, pp.69-78

Belge Tipi: Makale

Yayın Tarihi: 9/2019

Belge Dili: İngilizce

Document ID (Org No.): 2000639197

Sıklık: Aylık

eISSN: 1308-9099

pISSN: 1308-9080

Sayı

Yazarlar:

Gülcan GENCER | Kerem GENCER

Yayıncı:

Fırat University

Ana Başlıklar:

Doğal Bilimler

Dergi:

Turkish Journal of Science and Technology 2019 Vol.14 Issue 2, pp.69-78

Belge Tipi:

Makale

Yayın Tarihi:

9/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000639197

Sıklık:

Aylık

eISSN:

1308-9099

pISSN:

1308-9080