Modeling with bivariate geometric distributions

Jing Li, Sunil K. Dhar

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This article 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.

Original languageEnglish (US)
Pages (from-to)252-266
Number of pages15
JournalCommunications in Statistics - Theory and Methods
Volume42
Issue number2
DOIs
StatePublished - Jan 11 2013

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Keywords

  • Bayes estimation
  • Bivariate geometric distribution
  • Conditional failure rate
  • Maximum likelihood estimation

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