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Makale detayı · 2021 · article

Reliability estimation of the stress-strength model with non-identical jointly type-II censored Weibull component strengths

YÖKSİS OpenAlex
Yıl2021
Atıf9OpenAlex
Yüzdelik%80,2
FWCI1,221,00 = dünya ortalaması
Scopus (SJR)Q2
WoS (JCR)Q3

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıJournal of Statistical Computation and Simulation
  • Katalog eşleşmesi (ISSN)Journal of Statistical Computation and Simulation
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

This article considers the estimation of the stress–strength reliability with non-identical and also jointly censored component strengths. Both stress and strength variables are assumed to follow two-parameter Weibull distribution. In this reliability model, we assume type-II censoring scheme for common stress variable and jointly type-II censoring scheme for strength variables. Inferences for the reliability of this system are obtained with maximum likelihood estimation (MLE) and Bayesian estimation methods. In the Bayesian section, point estimations are obtained with Lindley's approximation and Markov Chain Monte Carlo method with the Metropolis-Hasting algorithm. Also, asymptotic confidence intervals for the MLEs and the highest posterior density credible intervals for Bayesian estimations are obtained. Theoretical outcomes are illustrated with simulation studies and a real data example.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

9atıfOpenAlex · cited_by_count (önbellek / veritabanı)

Yerel katalogda bu makaleye atıf yapan 2 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).

  1. 2024 Estimation of the Stress-Strength Parameter under Two-Sample Balanced Progressive Censoring SchemeAtıf 16 · OpenAlex
  2. 2023 Reliability estimation of a consecutive k-out-of-n system for non-identical strength components with applications to wind speed dataAtıf 16 · OpenAlex

Yazarlar

1
  1. ÇAĞATAY ÇETİNKAYA KIRIKKALE ÜNİVERSİTESİ 1