Title of article :
The Bivariate Modified Exponential Geometric Distribution: Model, Properties, and Applications
Author/Authors :
Zanbooria, A. R Department of Statistics - Islamic Azad University Marvdasht Branch, Marvdasht, Iran , Zarea, K Department of Statistics - Islamic Azad University Marvdasht Branch, Marvdasht, Iran , Khodadadia, Z Department of Statistics - Islamic Azad University Marvdasht Branch, Marvdasht, Iran
Abstract :
In this paper, we have introduced a five‐parameter bivariate model by taking a geometric
minimum of the modified exponential distributions. It is observed that the maximum likelihood
estimators of the unknown parameters cannot be obtained in closed form. We propose to use the
EM algorithm to compute the maximum likelihood estimators of the unknown parameters. Several
simulation experiments have been performed to determine the effectiveness of the proposed EM
algorithm. We analyzed two datasets for illustrative purposes, and it is observed that the proposed
models and the expectation‐maximization algorithm perform at a satisfactory level.
Keywords :
Expectation‐Maximization algorithm , Geometric minimum , Maximum likelihood estimation , Bivariate model
Journal title :
International Journal of Mathematical Modelling and Computations
