Bivariate Gumbel-G Family of Distributions: Statistical Properties, Bayesian and Non-Bayesian Estimation with Application

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Abstract

In this paper, a new class of bivariate distributions called the bivariate Gumbel-G family is proposed, whose marginal distributions are Gumbel-G families. Several of its statistical properties are derived. After introducing the general class, a special model of the new family is discussed in-detail. Bayesian and maximum likelihood techniques are used to estimate the model parameters. Simulation study is carried out to examine the bias and mean square error of Bayesian and maximum likelihood estimators. Finally, a real data set is analyzed for illustrative the flexibility of the proposed bivariate family.

Original languageEnglish
Pages (from-to)39-60
Number of pages22
JournalAnnals of Data Science
Volume6
Issue number1
DOIs
StatePublished - 7 Mar 2019
Externally publishedYes

Keywords

  • Bayesian estimation
  • Bivariate distributions
  • Gumbel-G family of distributions
  • Maximum likelihood estimation
  • Simulation

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