Scopus
🔓 Açık Erişim YÖKSİS Eşleşti
Modeling Voltage Real Data Set by a New Version of Lindley Distribution
IEEE Access · Ocak 2023
YÖKSİS Kayıtları
Modeling Voltage Real Data Set by a New Version of Lindley Distribution
IEEE Access · 2023 SCI-Expanded
DOÇENT KADİR KARAKAYA →
Modeling Voltage Real Data Set by a New Version of Lindley Distribution
IEEE Access · 2023 SCI-Expanded
DOÇENT KADİR KARAKAYA →
Makale Bilgileri
DergiIEEE Access
Yayın TarihiOcak 2023
Cilt / Sayfa11 · 67220-67229
Scopus ID2-s2.0-85162848362
Erişim🔓 Açık Erişim
Özet
This paper presents a novel probability distribution, namely the new XLindley distribution, derived from a unique combination of exponential and gamma distributions through a special mixture formulation. The study extensively investigates the mathematical properties of the proposed distribution, including but not limited to the moment generation function, moments of different orders, mode identification, and the quantile function. Furthermore, the research employs a Monte Carlo simulation to assess and compare the performance of various estimators in estimating the unknown parameter of the new XLindley distribution. These estimators are carefully evaluated and analyzed in terms of their efficiency and accuracy, providing valuable insights into the practical application of the new distribution in statistical modeling and data analysis contexts. The voltage and failure time data in the field of engineering are used to model the proposed distribution. The new model is compared with many current distributions such as Xlindley, gamma, Weibull, exponential, Lindley, Shanker, Akash, Zeghdoudi, Chris-Jerry, and Xgamma. Among all models, it is concluded that the new one-parameter distribution performed the best in modeling based on criteria such as the Akaike information criterion, Bayesian information criterion, and others. The real data results show that the proposed distribution exhibits greater flexibility and improved goodness of fit compared to alternative distributions. The new XLindley distribution could be useful in modeling real-life data and may warrant further exploration in future research. Overall, this study contributes to the field of probability distributions and provides new insights for statistical modeling.
Yazarlar (9)
1
Nawel Khodja
ORCID: 0009-0003-3339-1394
2
Ahmed M. Gemeay
3
Halim Zeghdoudi
ORCID: 0000-0002-4759-5529
4
Kadir Karakaya
5
Arwa M. Alshangiti
6
M. E. Bakr
7
Oluwafemi Samson Balogun
ORCID: 0000-0002-8870-9692
8
Abdisalam Hassan Muse
9
Eslam Hussam
Anahtar Kelimeler
estimation
Exponential distribution
quantile function
simulation
voltage data
XLindley distribution
Kurumlar
Amoud University
Borama Somalia
College of Sciences
Riyadh Saudi Arabia
Faculty of Science
Helwan Egypt
Faculty of Science
Tanta Egypt
Itä-Suomen yliopisto
Kuopio Finland
Selçuk Üniversitesi
Selçuklu Turkey
Université Badji Mokhtar - Annaba
Annaba Algeria
Metrikler
7
Atıf
9
Yazar
6
Anahtar Kelime