Bayesian estimation of a bivariate copula using the Jeffreys prior

DOI10.3150/10-BEJ345zbMath1318.62112arXiv0908.2372MaRDI QIDQ418233

François Perron, Simon Guillotte

Publication date: 28 May 2012

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0908.2372

zbMATH Keywords

copulaMarkov chain Monte Carlononparametricdoubly stochastic matricesBirkhoff polytopeobjective Bayesfinite mixturesMetropolis-within-Gibbs sampling

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Bayesian inference (62F15) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items

Bayesian estimation of generalized partition of unity copulas ⋮ Prior distributions for objective Bayesian analysis ⋮ Copula modelling with penalized complexity priors: the bivariate case ⋮ Bayesian nonparametrics for directional statistics ⋮ Bayesian nonparametric estimation of a copula

Uses Software

• QRM

Cites Work

• Extending the rank likelihood for semiparametric copula estimation
• An introduction to copulas.
• On rank correlation measures for non-continuous random variables
• Comparison of semiparametric and parametric methods for estimating copulas
• Strong approximation of copulas
• The Ehrhart polynomial of the Birkhoff polytope
• Asymptotic efficiency of the two-stage estimation method for copula-based models
• Density estimation
• Copula Modeling: An Introduction for Practitioners
• Bayesian inference for contingency tables with given marginals
• Results and problems in the theory of doubly-stochastic matrices
• THE BERNSTEIN COPULA AND ITS APPLICATIONS TO MODELING AND APPROXIMATIONS OF MULTIVARIATE DISTRIBUTIONS
• A semiparametric estimation procedure of dependence parameters in multivariate families of distributions
• A Primer on Copulas for Count Data
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