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Gumbel–Logistic Unit Distribution with Application in Telecommunications Data Modeling
by
Pažun, Brankica
, Langović, Zlatko
, Stojanović, Vladica S.
, Jovanović, Mihailo
, Grujčić, Željko
in
Asymmetry
/ Asymptotic properties
/ Distribution (Probability theory)
/ Distribution functions
/ Inequality
/ Logistics
/ Numerical analysis
/ Parameter estimation
/ Quantiles
/ Random variables
/ Simulation methods
/ Symmetry
/ Telecommunications
2024
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Gumbel–Logistic Unit Distribution with Application in Telecommunications Data Modeling
by
Pažun, Brankica
, Langović, Zlatko
, Stojanović, Vladica S.
, Jovanović, Mihailo
, Grujčić, Željko
in
Asymmetry
/ Asymptotic properties
/ Distribution (Probability theory)
/ Distribution functions
/ Inequality
/ Logistics
/ Numerical analysis
/ Parameter estimation
/ Quantiles
/ Random variables
/ Simulation methods
/ Symmetry
/ Telecommunications
2024
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Gumbel–Logistic Unit Distribution with Application in Telecommunications Data Modeling
by
Pažun, Brankica
, Langović, Zlatko
, Stojanović, Vladica S.
, Jovanović, Mihailo
, Grujčić, Željko
in
Asymmetry
/ Asymptotic properties
/ Distribution (Probability theory)
/ Distribution functions
/ Inequality
/ Logistics
/ Numerical analysis
/ Parameter estimation
/ Quantiles
/ Random variables
/ Simulation methods
/ Symmetry
/ Telecommunications
2024
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Gumbel–Logistic Unit Distribution with Application in Telecommunications Data Modeling
Journal Article
Gumbel–Logistic Unit Distribution with Application in Telecommunications Data Modeling
2024
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Overview
The manuscript deals with a new unit distribution that depends on two positive parameters. The distribution itself was obtained from the Gumbel distribution, i.e., by its transformation, using generalized logistic mapping, into a unit interval. In this way, the so-called Gumbel-logistic unit (abbr. GLU) distribution is obtained, and its key properties, such as cumulative distribution function, modality, hazard and quantile function, moment-based characteristics, Bayesian inferences and entropy, have been investigated in detail. Among others, it is shown that the GLU distribution, unlike the Gumbel one which is always positively asymmetric, can take both asymmetric forms. An estimation of the parameters of the GLU distribution, based on its quantiles, is also performed, together with asymptotic properties of the estimates thus obtained and their numerical simulation. Finally, the GLU distribution has been applied in modeling the empirical distributions of some real-world data related to telecommunications.
Publisher
MDPI AG
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