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The Additive Xgamma-Burr XII Distribution: Properties, Estimation and Applications
by
Salem, Heba N.
, EL-Helbawy, Abeer A.
, Alamri, Faten S.
, Mohammad, Hebatalla H.
in
Asymptotic methods
/ Confidence intervals
/ Distribution (Probability theory)
/ Flexibility
/ Hydrology
/ Maximum likelihood estimates
/ Parameters
/ Probability density functions
/ Reliability
/ Statistical analysis
/ Survival analysis
2024
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The Additive Xgamma-Burr XII Distribution: Properties, Estimation and Applications
by
Salem, Heba N.
, EL-Helbawy, Abeer A.
, Alamri, Faten S.
, Mohammad, Hebatalla H.
in
Asymptotic methods
/ Confidence intervals
/ Distribution (Probability theory)
/ Flexibility
/ Hydrology
/ Maximum likelihood estimates
/ Parameters
/ Probability density functions
/ Reliability
/ Statistical analysis
/ Survival analysis
2024
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Do you wish to request the book?
The Additive Xgamma-Burr XII Distribution: Properties, Estimation and Applications
by
Salem, Heba N.
, EL-Helbawy, Abeer A.
, Alamri, Faten S.
, Mohammad, Hebatalla H.
in
Asymptotic methods
/ Confidence intervals
/ Distribution (Probability theory)
/ Flexibility
/ Hydrology
/ Maximum likelihood estimates
/ Parameters
/ Probability density functions
/ Reliability
/ Statistical analysis
/ Survival analysis
2024
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The Additive Xgamma-Burr XII Distribution: Properties, Estimation and Applications
Journal Article
The Additive Xgamma-Burr XII Distribution: Properties, Estimation and Applications
2024
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Overview
This paper introduces a new four-parameter additive model, named xgamma-Burr XII distribution, by considering two competing risks: the former has the xgamma distribution and the latter has the Burr XII distribution. A graphical description of the xgamma-Burr XII distribution is presented, including plots of the probability density function, hazard rate and reversed hazard rate functions. The xgamma-Burr XII density has different shapes such as decreasing, unimodal, approximately symmetric and decreasing-unimodal. The main statistical properties of the proposed model are studied. The unknown model parameters, reliability, hazard rate and reversed hazard rate functions are estimated via the maximum likelihood method. The asymptotic confidence intervals of the parameters, reliability function, hazard rate function and reversed hazard rate function are also obtained. A simulation study is carried out to evaluate the performance of the maximum likelihood estimates. In addition, three real data are applied to show the superiority of the xgamma-Burr XII distribution over some known distributions in real-life applications.
Publisher
MDPI AG
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