The University of Southampton
University of Southampton Institutional Repository

Fitting discrete multivariate distributions with unbounded marginals and normal-copula dependence

Fitting discrete multivariate distributions with unbounded marginals and normal-copula dependence
Fitting discrete multivariate distributions with unbounded marginals and normal-copula dependence
In specifying a multivariate discrete distribution via the NORmal To Anything (NORTA) method, a problem of interest is: given two discrete unbounded marginals and a target value r, find the correlation of the bivariate Gaussian copula that induces rank correlation r between these marginals. By solving the analogous problem with the marginals replaced by finite-support (truncated) counterparts, an approximate solution can be obtained. Our main contribution is an upper bound on the absolute error, where error is defined as the difference between r and the resulting rank correlation between the original unbounded marginals. Furthermore, we propose a simple method for truncating the support while controlling the error via the bound, which is a sum of scaled squared tail probabilities. Examples where both marginals are discrete Pareto demonstrate considerable work savings against an alternative simple-minded truncation.
Avramidis, Athanassios
d6c4b6b6-c0cf-4ed1-bbe1-a539937e4001
Avramidis, Athanassios
d6c4b6b6-c0cf-4ed1-bbe1-a539937e4001

Avramidis, Athanassios (2009) Fitting discrete multivariate distributions with unbounded marginals and normal-copula dependence. Winter Simulation Conference, United States. 13 - 16 Dec 2009.

Record type: Conference or Workshop Item (Paper)

Abstract

In specifying a multivariate discrete distribution via the NORmal To Anything (NORTA) method, a problem of interest is: given two discrete unbounded marginals and a target value r, find the correlation of the bivariate Gaussian copula that induces rank correlation r between these marginals. By solving the analogous problem with the marginals replaced by finite-support (truncated) counterparts, an approximate solution can be obtained. Our main contribution is an upper bound on the absolute error, where error is defined as the difference between r and the resulting rank correlation between the original unbounded marginals. Furthermore, we propose a simple method for truncating the support while controlling the error via the bound, which is a sum of scaled squared tail probabilities. Examples where both marginals are discrete Pareto demonstrate considerable work savings against an alternative simple-minded truncation.

Text
wsc09ub.pdf - Other
Download (79kB)

More information

e-pub ahead of print date: 2009
Published date: 2009
Venue - Dates: Winter Simulation Conference, United States, 2009-12-13 - 2009-12-16
Organisations: Operational Research

Identifiers

Local EPrints ID: 150003
URI: https://eprints.soton.ac.uk/id/eprint/150003
PURE UUID: ae549703-7ac8-46ee-9d05-c617dca74edc
ORCID for Athanassios Avramidis: ORCID iD orcid.org/0000-0001-9310-8894

Catalogue record

Date deposited: 05 May 2010 09:08
Last modified: 24 Jul 2019 00:34

Export record

Contributors

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×