Approximate Bayesian Computation for Copula Estimation


  • Clara Grazian Università di Roma “La Sapienza”
  • Brunero Liseo Università di Roma “La Sapienza”



ABC algorithms, Multivariate distributions, Partially specified models


We describe a simple method for making inference on a functional of a multivariate distribution. The method is based on a copula representation of the multivariate distribution and it is based on the properties of an Approximate Bayesian Monte\,Carlo algorithm, where the proposed values of the functional of interest are weighed in terms of their empirical likelihood. This method is particularly useful when the 'true' likelihood function associated with the working model is too costly to evaluate or when the working model is only partially specified.


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How to Cite

Grazian, C., & Liseo, B. (2015). Approximate Bayesian Computation for Copula Estimation. Statistica, 75(1), 111–127.