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Objective priors for the number of degrees of freedom of a multivariate t distribution and the t-copula.

Lookup NU author(s): Dr Cristiano VillaORCiD

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Abstract

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.

Publication metadata

Author(s): Villa C, Rubio FJ

Publication type: Article

Publication status: Published

Journal: Computational Statistics and Data Analysis

Year: 2018

Volume: 124

Pages: 197-219

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

Publisher: Elsevier

URL: https://doi.org/10.1016/j.csda.2018.03.010

DOI: 10.1016/j.csda.2018.03.010

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