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Statistical inference of stress-strength reliability for the exponential power (EP) distribution based on progressive type-II censored samples

Hacettepe Journal of Mathematics and Statistics · Ocak 2017

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YÖKSİS Kayıtları
Statistical inference of stress-strength reliability for the exponential power (EP) distribution based on progressive type-II censored samples
Hacettepe Journal of Mathematics and Statistics · 2017 SCI-Expanded
PROFESÖR BUĞRA SARAÇOĞLU →
Statistical inference of stress-strength reliability for the exponential power (EP) distribution based on progressive type-II censored samples
Hacettepe Journal of Mathematics and Statistics · 2017 SCI-Expanded
DOKTOR ÖĞRETİM ÜYESİ NERİMAN AKDAM →
Statistical inference of stress-strength reliability for the exponential power (EP) distribution based on progressive type-II censored samples
Hacettepe Journal of Mathematics and Statistics · 2017 SCI-Expanded
PROFESÖR İSMAİL KINACI →

Makale Bilgileri

DergiHacettepe Journal of Mathematics and Statistics
Yayın TarihiOcak 2017
Cilt / Sayfa46 · 239-253
Erişim🔓 Açık Erişim
Özet Suppose that X represents the stress which is applied to a component and Y is strength of this component. Let X and Y have Exponential Power (EP) distribution with (α1, β1) and (α2, β2) parameters, respectively. In this case, stress-strength reliability (SSR) is shown by P = P (X < Y). In this study, the SSR for EP distribution are obtained with numerical methods. Also maximum likelihood estimate (MLE) and approximate bayes estimates by using Lindley approximation method under squared-error loss function for SSR under progressive type-II censoring are obtained. Moreover, performances of these estimators are compared in terms of MSEs by using Monte Carlo simulation. Furthermore coverage probabilities of parametric bootstrap estimates are computed. Finally, real data analysis is presented.

Yazarlar (3)

1
Neriman Akdam
2
İsmail Kınacı
3
Buğra Saraçoğlu

Anahtar Kelimeler

Bayes estimation Bootstrap estimation Exponential Power distribution Lindley’s approximation Maximum likelihood estimation Monte Carlo simulation

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey

Metrikler

14
Atıf
3
Yazar
6
Anahtar Kelime

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