Scopus
🔓 Açık Erişim YÖKSİS DOI Eşleşti
SJR Q2
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
Pakistan Journal of Statistics and Operation Research · Ocak 2024
YÖKSİS Kayıtları
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
Pakistan Journal of Statistics and Operation Research · 2024 ESCI
Doç. Dr. YUNUS AKDOĞAN →
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
Pakistan Journal of Statistics and Operation Research · 2024 ESCI
Doç. Dr. KADİR KARAKAYA →
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
Pakistan Journal of Statistics and Operation Research · 2024
Prof. Dr. BUĞRA SARAÇOĞLU →
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
Pakistan Journal of Statistics and Operation Research · 2024 ESCI
Prof. Dr. COŞKUN KUŞ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
2024 ISSN: 1816-2711 ESCI
Doç. Dr. KADİR KARAKAYA →
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
2024 ISSN: 1816-2711 ESCI
Doç. Dr. YUNUS AKDOĞAN →
Statistical Inference on Process Capability Index Cpyk for Inverse Rayleigh Distribution under Progressive Censoring
2024 ISSN: 1816-2711 Q3
Prof. Dr. BUĞRA SARAÇOĞLU →
Makale Bilgileri
ISSN18162711
Yayın TarihiOcak 2024
Cilt / Sayfa20 · 37-47
Scopus ID2-s2.0-85189461224
Erişim🔓 Açık Erişim
Özet
In quality engineering, process capability indices play a crucial role in assessing the capability of a given process. Among the widely recognized indices are Cp, Cpk, Cpm, and Cpmk, all of which presuppose the normality of the product lifetime. However, Maiti et al. (2010) proposed a more versatile process capability index, denoted as Cpyk, which does not rely on distributional assumptions. The study is currently investigating statistical inferences for the Cpyk index within the context of progressively type-II censored samples, marking the first exploration of this aspect in the research. This paper investigates maximum likelihood and Bayesian inference for the Cpyk when the underlying distribution follows the inverse Rayleigh distribution. Additionally, the study explores Bayesian credible intervals and the highest posterior density intervals using the Markov Chain Monte Carlo procedure. Various types of bootstrap confidence intervals are also taken into consideration. To assess the performance of these intervals, a Monte Carlo simulation is executed, comparing their coverage probabilities and mean lengths. The paper concludes with an illustrative example utilizing real data, providing a practical application of the discussed methodologies.
Yazarlar (5)
1
Kadir Karakaya
2
İsmail Kınacı
3
Yunus Akdoğan
4
Buğra Saraçoğlu
5
Coşkun Kuş
Anahtar Kelimeler
Bayesian Estimation
Bootstrap
Capability Index
Confidence Interval
Monte Carlo Simulation
Progressive Censoring
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Pakistan Journal of Statistics and Operation Research
Q2
OA
SJR Skoru0,575
H-Index32
YayıncıUniversity of Punjab (new Campus)
ÜlkePakistan
Management Science and Operations Research (Q2)
Modeling and Simulation (Q2)
Statistics and Probability (Q2)
Statistics, Probability and Uncertainty (Q2)
Metrikler
4
Atıf
5
Yazar
6
Anahtar Kelime