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Inference on process capability index Spmk for a new lifetime distribution

Soft Computing · Ekim 2024

Özet
In various applied disciplines, the modeling of continuous data often requires the use of flexible continuous distributions. Meeting this demand calls for the introduction of new continuous distributions that possess desirable characteristics. This paper introduces a new continuous distribution. Several estimators for estimating the unknown parameters of the new distribution are discussed and their efficiency is assessed through Monte Carlo simulations. Furthermore, the process capability index Spmk is examined when the underlying distribution is the proposed distribution. The maximum likelihood estimation of the Spmk is also studied. The asymptotic confidence interval is also constructed for Spmk. The simulation results indicate that estimators for both the unknown parameters of the new distribution and the Spmk provide reasonable results. Some practical analyses are also performed on both the new distribution and the Spmk. The results of the conducted data analysis indicate that the new distribution yields effective outcomes in modeling lifetime data in the literature. Similarly, the data analyses performed for Spmk illustrate that the new distribution can be utilized for process capability indices by quality controllers.
3 atıf Ekim 2024 DOI
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YÖKSİS Kayıtları
Inference on process capability index Spmk for a new lifetime distribution
Soft Computing · 2024 SCI-Expanded
Doç. Dr. KADİR KARAKAYA →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Bu dergide (ISSN eşleşmesi) kurumun 3 kaydı bulundu.
A comprehensive comparison of accuracy-based fitness functions of metaheuristics for feature selection
2023 ISSN: 1432-7643 SCI-Expanded Q2
Doç. Dr. AHMET CEVAHİR ÇINAR →
Inference on process capability index Spmk for a new lifetime distribution
2024 ISSN: 1432-7643 SCI-Expanded Q2
Doç. Dr. KADİR KARAKAYA →
Multiple arbitrarily inflated negative binomial regression model and its application
2024 ISSN: 1432-7643 SCI-Expanded Q2
Prof. Dr. COŞKUN KUŞ →

Makale Bilgileri

Toplam Atıf 3 atıf · Scopus
ISSN14327643
Yayın TarihiEkim 2024
Cilt / Sayfa28 · 10929-10941
Erişim🔓 Açık Erişim

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey

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Scimago Dergi (ISSN Eşleşmesi)
Soft Computing
Q2
SJR Skoru0,656
H-Index130
YayıncıSpringer Science and Business Media Deutschland GmbH
ÜlkeGermany
Geometry and Topology (Q2)
Software (Q2)
Theoretical Computer Science (Q2)
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