Strathprints logo
Strathprints Home | Open Access | Browse | Search | User area | Copyright | Help | Library Home | SUPrimo

Approximating multivariate distributions with vines

Bedford, T.J. and Daneshkhah, A. (2010) Approximating multivariate distributions with vines. Working paper. Management Science Working Series. (In Press)

PDF (strathprints028364.pdf)

Download (1MB) | Preview


In a series of papers, Bedford and Cooke used vine (or pair-copulae) as a graphical tool for representing complex high dimensional distributions in terms of bivariate and conditional bivariate distributions or copulae. In this paper, we show that how vines can be used to approximate any given multivariate distribution to any required degree of approximation. This paper is more about the approximation rather than optimal estimation methods. To maintain uniform approximation in the class of copulae used to build the corresponding vine we use minimum information approaches. We generalised the results found by Bedford and Cooke that if a minimal information copula satis¯es each of the (local) constraints (on moments, rank correlation, etc.), then the resulting joint distribution will be also minimally informative given those constraints, to all regular vines. We then apply our results to modelling a dataset of Norwegian financial data that was previously analysed in Aas et al. (2009).

Item type: Monograph (Working paper)
ID code: 28364
Keywords: multivariate distribution, vines, bivariate distributions, management science, Management. Industrial Management
Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
Department: Strathclyde Business School > Management Science
Depositing user: Mrs Caroline Sisi
Date Deposited: 22 Oct 2010 12:51
Last modified: 24 Jul 2015 11:20

Actions (login required)

View Item View Item