Copula Bayesian Networks

Gal Elidan
2010 Neural Information Processing Systems  
We present the Copula Bayesian Network model for representing multivariate continuous distributions, while taking advantage of the relative ease of estimating univariate distributions. Using a novel copula-based reparameterization of a conditional density, joined with a graph that encodes independencies, our model offers great flexibility in modeling high-dimensional densities, while maintaining control over the form of the univariate marginals. We demonstrate the advantage of our framework for
more » ... generalization over standard Bayesian networks as well as tree structured copula models for varied real-life domains that are of substantially higher dimension than those typically considered in the copula literature.
dblp:conf/nips/Elidan10 fatcat:gsmhpxqskvg6jdyjsqi3bnofra