✨
AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Its performance is illustrated by means of two real data sets.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:In this paper, a new family of distributions, called the Kumaraswamy odd log-logistic, is proposed and studied.
📊
Key Findings & Data:Some mathematical properties are presented and special models are discussed.
💡
Conclusion & Impact:Its performance is illustrated by means of two real data sets.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Generated function · Log-logistic distribution · Maximum likelihood
Abstract
In this paper, a new family of distributions, called the Kumaraswamy odd log-logistic, is proposed and studied. Some mathematical properties are presented and special models are discussed. The asymptotes and shapes are investigated. The family density function is given by a linear combination of exponentiated densities following the same baseline model. We derive a power series for the quantile function, explicit expressions for the moments, quantile and generating functions and order statistics. We provide a bivariate extension of the new family. Its performance is illustrated by means of two real data sets.
Keywords
🔖
Cite This Article
Alizadeh, M., Doostparast, M., Emadi, M., M.Cordeiro, G., M.M.Ortegak, E., R.Pescim, R. (2022). A new family of distributions: the Kumaraswamy odd log-logistic, properties and applications. Hacettepe Journal of Mathematics and Statistics, Cilt: 44 - Sayı: 6, 1491–1512. https://ajindex.com/articles/528982