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Emrah Altun
Researcher at Bartın University
Publications - 83
Citations - 1077
Emrah Altun is an academic researcher from Bartın University. The author has contributed to research in topics: Regression analysis & Quantile. The author has an hindex of 14, co-authored 79 publications receiving 659 citations. Previous affiliations of Emrah Altun include Hacettepe University.
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The generalized odd log-logistic family of distributions: properties, regression models and applications
TL;DR: In this article, a new class of continuous distributions with two extra shape parameters named the generalized odd log-logistic family of distributions was proposed, which can be expressed as a linear combination of exponentiated densities based on the same baseline distribution.
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A new family of distributions with properties, regression models and applications
Haitham M. Yousof,Emrah Altun,Thiago G. Ramires,Thiago G. Ramires,Morad Alizadeh,Mahdi Rasekhi +5 more
TL;DR: In this paper, the authors introduced a new family of continuous distributions with one extra shape parameter, called the Burr-Hatke-G family, based on the BH differential equation.
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A New Extended G Family of Continuous Distributions with Mathematical Properties, Characterizations and Regression Modeling
TL;DR: In this article, a new extended G family of distributions is proposed and the maximum likelihood method is used to estimate the model parameters by means of graphical and numerical Monte Carlo simulation study.
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The Odd Power Lindley Generator of Probability Distributions: Properties, Characterizations and Regression Modeling
TL;DR: In this paper, a new flexible family of distributions is proposed with its statistical properties as well as some useful characterizations, and the maximum likelihood method is used to estimate the unknown model parameters by means of two simulation studies.
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Discrete Burr-Hatke Distribution With Properties, Estimation Methods and Regression Model
TL;DR: A new one-parameter discrete distribution, namely discrete Burr-Hatke distribution is introduced and its mathematical properties are studied comprehensively and it opens a new opportunity to model over-dispersed data sets.