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Lookup NU author(s): Dr Cristiano VillaORCiD
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An objective Bayesian approach to estimate the number of degrees of freedom for the multivariate distribution and for the -copula, when the parameter is considered discrete, is proposed. Inference on this parameter has been problematic for the multivariate and, for the absence of any method, for the -copula. An objective criterion based on loss functions which allows to overcome the issue of defining objective probabilities directly is employed. The support of the prior for is truncated, which derives from the property of both the multivariate and the -copula of convergence to normality for a sufficiently large number of degrees of freedom. The performance of the priors is tested on simulated scenarios 1and on real data: daily logarithmic returns of IBM and of the Center for Research in Security Prices Database.
Author(s): Villa C, Rubio FJ
Publication type: Article
Publication status: Published
Journal: Computational Statistics and Data Analysis
Print publication date: 01/08/2018
Online publication date: 27/03/2018
Acceptance date: 13/03/2018
ISSN (print): 0167-9473
ISSN (electronic): 1872-7352
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