Is eliciting dependency worth the effort? A study for the multivariate Poisson-Gamma probability model

2021/11/23 by Rafael Schwarzenegger, John Quigley, Lesley Walls · 1 citation
Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Artificial intelligence #Bayes' theorem #Bayesian probability #Computer science #Dependency (UML) #Econometrics #Estimator #Forecasting Techniques and Applications #Mathematics #Multivariate statistics #Optimal Experimental Design Methods #Poisson distribution #Reliability (semiconductor) #Statistics

paper · pdf · doi:10.1177/1748006x211059417

openalex publication_date 2021/11/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/02

Abstract

We examine whether it is worthwhile eliciting subjective judgements to account for dependency in a multivariate Poisson-Gamma probability model. The challenge of estimating reliability during product design motivated the choice of model class. For the multivariate Poisson-Gamma model we adopt an empirical Bayes methodology to present an estimator with improved accuracy. A simulation study investigates the estimation error of this estimator for different degrees of dependency and examines the impact of dependency being mis-specified when assessed by subjective judgement. Our theoretical and simulation findings give analysts insights about the value of eliciting dependency.

Citations

• Uncertain Judgements: Eliciting Experts' Probabilities
• A Bayes Linear Bayes Method for Estimation of Correlated Event Rates

Cited by

• Poisson regression [wikipedia]

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