Hierarchical EM algorithm for estimating the parameters of Mixture of Bivariate Generalized Exponential distributions

TL;DR

This paper introduces a hierarchical EM algorithm to estimate parameters of a mixture model based on the bivariate generalized exponential distribution, addressing large sample sizes and demonstrating its properties and effectiveness.

Contribution

The paper develops a novel hierarchical EM algorithm specifically for mixture models of bivariate generalized exponential distributions, enhancing parameter estimation methods.

Findings

Algorithm effectively estimates parameters for large samples.

Properties of the mixture distribution are thoroughly studied.

Numerical results validate the proposed method.

Abstract

This paper provides a mixture modeling framework using the bivariate generalized exponential distribution. We study different properties of this mixture distribution. Hierarchical EM algorithm is developed for finding the estimates of the parameters. The algorithm takes very large sample size to work as it contains many stages of approximation. Numerical Results are provided for more illustration.