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Journal of Data Science


Computational Challenges of t and Related Copulas
Volume 20, Issue 1 (2022), pp. 95–110
Pub. online: 2 February 2022      Type: Computing In Data Science      Open accessOpen Access
Received
5 January 2022
Accepted
6 January 2022
Published
2 February 2022

Abstract

The present paper addresses computational and numerical challenges when working with t copulas and their more complicated extensions, the grouped t and skew t copulas. We demonstrate how the R package nvmix can be used to work with these copulas. In particular, we discuss (quasi-)random sampling and fitting. We highlight the difficulties arising from using more complicated models, such as the lack of availability of a joint density function or the lack of an analytical form of the marginal quantile functions, and give possible solutions along with future research ideas.

Supplementary material

 Supplementary Material
This paper can be reproduced with the R script reproduce.R and the R package nvmix, version 0.0-7.

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Copyright
2022 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.
Open access article under the CC BY license.

Keywords
copulas density distribution function estimation sampling

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