Generalization of Log-Logistic Family with Quantile Regression Model
Mathematical and Computational Applications, cilt.31, sa.1, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 31 Sayı: 1
- Basım Tarihi: 2026
- Doi Numarası: 10.3390/mca31010007
- Dergi Adı: Mathematical and Computational Applications
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, INSPEC, zbMATH, Directory of Open Access Journals
- Anahtar Kelimeler: logistic distribution, maximum likelihood estimation, regression, residuals, simulation
- Gazi Üniversitesi Adresli: Evet
Özet
A new general class of distributions is proposed by applying the transformation to the random variable that follows the generalized odd-logistic family. Using the proposed family, we introduce a flexible Weibull distribution. The importance of the proposed distribution is demonstrated and compared with different generalizations of the Weibull distribution via three real data applications. A quantile regression model is obtained using the newly developed Weibull model and compared with the standard Weibull quantile regression model through a real data application.