Eliciting Dirichlet and Gaussian copula prior distributions for multinomial models

DOI10.1007/s11222-016-9632-7zbMath1505.62134OpenAlexW2285598936WikidataQ59615065 ScholiaQ59615065MaRDI QIDQ518253

Fadlalla G. Elfadaly, Paul H. Garthwaite

Publication date: 28 March 2017

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-016-9632-7

zbMATH Keywords

Dirichlet distributionprior distributionmultinomial modelelicitation methodinteractive graphical softwareGaussian copula elicitation

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (7)

Recent Advances in the Elicitation of Uncertainty Distributions from Experts for Multinomial Probabilities ⋮ Specification of informative prior distributions for multinomial models using vine copulas ⋮ Subjective elicitation of hyperparameters of a conjugate Dirichlet prior and the corresponding Bayes analysis ⋮ Stochastic sensitivity analysis of concentration measures ⋮ Copula modelling with penalized complexity priors: the bivariate case ⋮ Checking for model failure and for prior-data conflict with the constrained multinomial model ⋮ Structured priors for sparse probability vectors with application to model selection in Markov chains

Uses Software

• WinBUGS
• PEGS
• elicit-normlin

Cites Work

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• Prior distribution elicitation for generalized linear and piecewise-linear models
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• Concepts of Independence for Proportions with a Generalization of the Dirichlet Distribution
• Copula Models for Aggregating Expert Opinions
• Understanding Relationships Using Copulas
• Statistical Methods for Eliciting Probability Distributions

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