Abstract
In this work, we construct a new bivariate statistical distribution by the conditionally specified model approach. The conditional distributions follow the well-known generalized exponential distribution which includes the ordinary exponential distribution and is more flexible than gamma and Weibull in some ways. The newly defined distribution has four parameters that increase the flexibility of the model in data fitting. By equating the dependence parameter to zero, the marginal distributions become independent generalized exponential distributions. The new bivariate distribution depends on the classical exponential integral function which is not difficult to evaluate numerically. The basic properties of the distribution such as distribution functions, moments and stress-strength reliability are derived. The parameters are estimated by the method of maximum likelihood. Two real data fitting applications prove its usefulness in case of negatively correlated bivariate data modelling.
Acknowledgement
The third author acknowledge the grant of the Ministry of Education, Science and Technological Development of Serbia 451-03-47/2023-01/200124 for carrying out this research.
Communicated by Gejza Wimmer
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© 2024 Mathematical Institute Slovak Academy of Sciences
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Articles in the same Issue
- On the Paley graph of a quadratic character
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- A general formula in composition theory
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- Digital Jordan surfaces arising from tetrahedral tiling
- Influence of ideals in compactifications
- On the functions ωf and Ωf
- On the 𝓐-generators of the polynomial algebra as a module over the Steenrod algebra, I
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