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The Weibull-Gamma Distribution: Properties and Applications [PDF]
A new member of the Weibull-generated (Weibull-G) family of distributions—namely the Weibull-gamma distribution—is proposed. This four-parameter distribution can provide great flexibility in modeling different data distribution shapes.
Hadeel S. Klakattawi
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Multivariate Extended Gamma Distribution
In this paper, I consider multivariate analogues of the extended gamma density, which will provide multivariate extensions to Tsallis statistics and superstatistics.
Dhannya P. Joseph
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Recently, artificial intelligence applications in magnetic resonance imaging have been applied in several clinical studies. The analysis of brain tumors without human intervention is considered a significant area of research because the extracted brain ...
Gunasekaran Manogaran +4 more
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AbstractJohn Dagpunar introduces a probability distribution to model real-valued positive measurements, such as time spent queuing for a taxi or waiting for a hospital ...
J. Dagpunar
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Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas. [PDF]
Togao O +11 more
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SIFAT-SIFAT DAN KEJADIAN KHUSUS DISTRIBUSI GAMMA
The gamma distribution is one of special continuous random variable distribution with scale parameter and shape parameter where is positive real numbers.
Royke Yohanes Warella +2 more
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A bimatrix variate gamma distribution
In this article, a bimatrix gamma distributions is introduced. Various mathematical properties of the proposed distribution like marginal distributions, expected values, entropies, and moment generating function are derived.
Maryam Rafiei +4 more
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A comprehensive toolbox for the gamma distribution: The gammadist package
The gamma distribution is one of the most important parametric models in probability theory and statistics. Although a multitude of studies have theoretically investigated the properties of the gamma distribution in the literature, there is still a ...
Piao Chen, Kilian Buis, Xiujie Zhao
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In the absence of a correct distribution theory for complex data, neutrosophic algebra can be very useful in quantifying uncertainty. In applied data analysis, implementation of existing gamma distribution becomes inadequate for some applications when ...
Zahid Khan +3 more
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