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Unit Exponential Probability Distribution: Characterization and Applications in Environmental and Engineering Data Modeling
by
Bakouch, Hassan S.
, Stojanović, Vladica S.
, Hussain, Tassaddaq
, Tošić, Marina
, Qarmalah, Najla
in
characterizations
/ Distribution (Probability theory)
/ Distribution functions
/ Environmental engineering
/ estimation
/ hazard function
/ Mathematical models
/ Monte Carlo simulation
/ Parameter estimation
/ Probability distribution functions
/ Quantiles
/ Random variables
/ simulation
/ Skewness
/ Statistical analysis
/ statistical model
/ Statistical tests
/ unit distribution
2023
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Unit Exponential Probability Distribution: Characterization and Applications in Environmental and Engineering Data Modeling
by
Bakouch, Hassan S.
, Stojanović, Vladica S.
, Hussain, Tassaddaq
, Tošić, Marina
, Qarmalah, Najla
in
characterizations
/ Distribution (Probability theory)
/ Distribution functions
/ Environmental engineering
/ estimation
/ hazard function
/ Mathematical models
/ Monte Carlo simulation
/ Parameter estimation
/ Probability distribution functions
/ Quantiles
/ Random variables
/ simulation
/ Skewness
/ Statistical analysis
/ statistical model
/ Statistical tests
/ unit distribution
2023
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Unit Exponential Probability Distribution: Characterization and Applications in Environmental and Engineering Data Modeling
by
Bakouch, Hassan S.
, Stojanović, Vladica S.
, Hussain, Tassaddaq
, Tošić, Marina
, Qarmalah, Najla
in
characterizations
/ Distribution (Probability theory)
/ Distribution functions
/ Environmental engineering
/ estimation
/ hazard function
/ Mathematical models
/ Monte Carlo simulation
/ Parameter estimation
/ Probability distribution functions
/ Quantiles
/ Random variables
/ simulation
/ Skewness
/ Statistical analysis
/ statistical model
/ Statistical tests
/ unit distribution
2023
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Unit Exponential Probability Distribution: Characterization and Applications in Environmental and Engineering Data Modeling
Journal Article
Unit Exponential Probability Distribution: Characterization and Applications in Environmental and Engineering Data Modeling
2023
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Overview
Distributions with bounded support show considerable sparsity over those with unbounded support, despite the fact that there are a number of real-world contexts where observations take values from a bounded range (proportions, percentages, and fractions are typical examples). For proportion modeling, a flexible family of two-parameter distribution functions associated with the exponential distribution is proposed here. The mathematical and statistical properties of the novel distribution are examined, including the quantiles, mode, moments, hazard rate function, and its characterization. The parameter estimation procedure using the maximum likelihood method is carried out, and applications to environmental and engineering data are also considered. To this end, various statistical tests are used, along with some other information criterion indicators to determine how well the model fits the data. The proposed model is found to be the most efficient plan in most cases for the datasets considered.
Publisher
MDPI AG
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