We describe a simple method for making inference on a functional of a multivariate distri- bution. The method is based on a copula representation of the multivariate distribution and it is based on the properties of an Approximate Bayesian MonteCarlo algorithm, where the proposed values of the functional of interest are weighed in terms of their em- pirical 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.
Approxiamte Bayesian Methods for copula estimation / Grazian, Clara; Liseo, Brunero. - In: STATISTICA. - ISSN 1973-2201. - STAMPA. - 75:1(2015), pp. 111-127.
Approxiamte Bayesian Methods for copula estimation
GRAZIAN, CLARAPrimo
Methodology
;LISEO, Brunero
Ultimo
Methodology
2015
Abstract
We describe a simple method for making inference on a functional of a multivariate distri- bution. The method is based on a copula representation of the multivariate distribution and it is based on the properties of an Approximate Bayesian MonteCarlo algorithm, where the proposed values of the functional of interest are weighed in terms of their em- pirical 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.| File | Dimensione | Formato | |
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