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 language | English |
|---|---|
| Pages (from-to) | 39-60 |
| Number of pages | 22 |
| Journal | Annals of Data Science |
| Volume | 6 |
| Issue number | 1 |
| DOIs | |
| State | Published - 7 Mar 2019 |
| Externally published | Yes |
Keywords
- Bayesian estimation
- Bivariate distributions
- Gumbel-G family of distributions
- Maximum likelihood estimation
- Simulation
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