Dependence models arising from the lagrangian probability distributions

Shubiao Li, Dennis Black, Carl Lee, Felix Famoye, Sung Li

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In this article, we propose a method based on the Lagrangian probability distributions for developing new dependence models. Specifically, a generalized Poisson-gamma dependence model is derived. The maximum likelihood estimation (MLE) technique is proposed for estimating the dependence model parameters. Application of the generalized Poisson-gamma dependence model is illustrated by using an operational risks dataset.

Original languageEnglish
Pages (from-to)1729-1742
Number of pages14
JournalCommunications in Statistics - Theory and Methods
Volume39
Issue number10
DOIs
StatePublished - Jun 2010

Keywords

  • Conditional independence
  • Discrete model
  • Estimation
  • Operational risk

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