Trivariate Burr-III copula with applications to income data

Capitani, Lucio De; Nicolussi, Federica; Zini, Alessandro

doi:10.1007/s40300-016-0104-9

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Ismail and Khalid [8] used some copulas as Ali-Mikhail-Haq, Clayton and Gumbel based on uncensored data to joint specific BBIII and Burr Type XII distributions by using theorem and algorithm of construction. Capitani et al [9] showed a bivariate Burr Type III copula to the trivariate case. Ogana et al [10] considered Frank and Plackett copulas; the two copulas were evaluated on seven distributions models using data from temperate and tropical forests where one of the seven distributions is BBIII distribution.…”

Section: Original Research Articlementioning

confidence: 99%

Bivariate Burr Type III Distribution: Estimation and Prediction

Mahmoud

Refaey

AL-Dayian

et al. 2021

JAMCS

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In this paper, a bivariate Burr Type III distribution is constructed and some of its statistical properties such as bivariate probability density function and its marginal, joint cumulative distribution and its marginal, reliability and hazard rate functions are studied. The joint probability density function and the joint cumulative distribution are given in closed forms. The joint expectation of this distribution is proposed. The maximum likelihood estimation and prediction for a future observation are derived. Also, Bayesian estimation and prediction are considered under squared error loss function. The performance of the proposed bivariate distribution is examined using a simulation study. Finally, a data set is analyzed under the proposed distribution to illustrate its flexibility for real-life application.

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Section: Original Research Articlementioning

confidence: 99%

Bivariate Burr Type III Distribution: Estimation and Prediction

Mahmoud

Refaey

AL-Dayian

et al. 2021

JAMCS

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show abstract

“…The methodology is based on the derivation of the parametric forms of a probability density function (pdf) and cumulative distribution function (cdf) for this family of distributions. Ismail and Khalid (2015) used some copulas as Ali-Mikhail-Haq (AMH), Clayton and Gumbel on uncensored data to joint specific Burr Type III and XII distributions using theorem and algorithm of construction the copula Capitani et al (2016) showed a bivariate Burr III copula to the trivariate case. This copula seems to be very general and analytically manageable and it provides an alternative to the commonly employed elliptical copulas (such as the Gaussian or the Student , sons since they have, roughly the same number of parameters.…”

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confidence: 99%

A Study on Bivariate Burr Tybe Iii Distribution

Refaey

Mahmoud²

2021

المجلة العلمیة لقطاع کلیات التجارة

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Burr Type III distribution have been mainly used in statistical modeling of events in a variety of applied mathematical contexts such as fracture roughness, life testing, meteorology, modeling crop prices, forestry, reliability analysis. Our aim of this work is to construct a bivariate Burr Type III distribution and some of its structural properties such as bivariate probability density function and it ' s marginal, joint cumulative distribution and it ' s marginal, reliability and hazard rate function are studied. The maximum likelihood estimators of the parameters are derived. The Bayes estimators of the parameters based on the squared error loss function and Bayesian prediction of the future observations are presented. The performance of the proposed bivariate distribution is examined using a simulation study. Finally, one data set under the proposed distributions to illustrate their flexibility for real-life applications is analyzed.

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MATLAB tool for probability density assessment and nonparametric estimation

Farmer

Jacobs

2022

SoftwareX

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Trivariate Burr-III copula with applications to income data

Cited by 3 publications

References 7 publications

Bivariate Burr Type III Distribution: Estimation and Prediction

Bivariate Burr Type III Distribution: Estimation and Prediction

A Study on Bivariate Burr Tybe Iii Distribution

MATLAB tool for probability density assessment and nonparametric estimation

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