A BIVARIATE KUMARASWAMY-EXPONENTIAL DISTRIBUTION WITH APPLICATION
In this paper, we introduce a new bivariate Kumaraswamy exponential distribution, whose marginals are univariate Kumaraswamy exponential. Some probabilistic properties of this bivariate distribution are derived, such as joint density function, marginal density functions, conditional density function...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Institución: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unesp.br:11449/194888 |
| Acceso en línea: | http://dx.doi.org/10.1515/ms-2017-0300 http://hdl.handle.net/11449/194888 |
| Access Level: | acceso abierto |
| Palabra clave: | bivariate Kumaraswamy-exponential distribution marginal and conditional density functions moments stress-strength maximum likelihood Fisher information matrix Bayesian estimation |
| Sumario: | In this paper, we introduce a new bivariate Kumaraswamy exponential distribution, whose marginals are univariate Kumaraswamy exponential. Some probabilistic properties of this bivariate distribution are derived, such as joint density function, marginal density functions, conditional density functions, moments and stress-strength reliability. Also, we provide the expected information matrix with its elements in a closed form. Estimation of the parameters is investigated by the maximum likelihood, Bayesian and least squares estimation methods. A simulation study is carried out to compare the performance of the estimators by estimation methods. Further, one data set have been analyzed to show how the proposed distribution works in practice. (C) 2019 Mathematical Institute Slovak Academy of Sciences |
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