Bivariate generalized exponential distribution |
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| Authors: | Debasis Kundu Rameshwar D Gupta |
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| Institution: | 1. Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, Pin 208016, India;2. Department of Computer Science and Statistics, The University of New Brunswick at Saint John, New Brunswick, Canada E2L 4L5 |
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| Abstract: | Recently it has been observed that the generalized exponential distribution can be used quite effectively to analyze lifetime data in one dimension. The main aim of this paper is to define a bivariate generalized exponential distribution so that the marginals have generalized exponential distributions. It is observed that the joint probability density function, the joint cumulative distribution function and the joint survival distribution function can be expressed in compact forms. Several properties of this distribution have been discussed. We suggest to use the EM algorithm to compute the maximum likelihood estimators of the unknown parameters and also obtain the observed and expected Fisher information matrices. One data set has been re-analyzed and it is observed that the bivariate generalized exponential distribution provides a better fit than the bivariate exponential distribution. |
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