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Activity Number: 61
Type: Topic Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: Government Statistics Section
Abstract #320283
Title: Modeling with Bivariate Geometric Distributions
Author(s): Jing Li*
Companies:
Keywords: Bivariate geometric distribution ; Bayes estimation ; Conditional failure rate ; Maximum likelihood estimation
Abstract:

This presentation describes two bivariate geometric distributions. We investigate characterizations of bivariate geometric distributions using conditional failure rates and study properties of the bivariate geometric distributions. The bivariate models are fitted to real-life data using the Method of Moments, Maximum Likelihood, and Bayes Estimators. Two methods of moments estimators, in each bivariate geometric model, are compared and evaluated for their performance in terms of bias vector and covariance matrix. This comparison is done through a Monte Carlo simulation. Chi-square goodness-of-fit tests are used to evaluate model performance.


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