Properties of the NORTA method in higher dimensions

Author

Ghosh, Soumyadip ; Henderson, Shane G.

Author_Institution

Sch. of Operations Res. & Ind. Eng., Cornell Univ., Ithaca, NY, USA

Volume

1

fYear

2002

fDate

8-11 Dec. 2002

Firstpage

263

Abstract

The NORTA method for multivariate generation is a fast general purpose method for generating samples of a random vector with given marginal distributions and given product-moment or rank correlation matrix. However, this method has been shown to fail to work for some feasible correlation matrices. (A matrix is feasible if there exists a random vector with the given marginal distributions and the matrix as the correlation matrix.) We investigate how this feasibility problem behaves as the dimension of the random vector is increased and find the problem to become acute rapidly. We also find that a modified NORTA procedure, augmented by a semidefinite program (SDP) that aims to generate a correlation matrix "close" to the desired one, performs well with increasing dimension.

Keywords

matrix algebra; random processes; vectors; NORTA method; correlation matrices; marginal distributions; multivariate generation; product moment; random vector; rank correlation matrix; semidefinite program; Density measurement; Distributed computing; Distribution functions; Industrial engineering; Operations research; Risk analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference, 2002. Proceedings of the Winter

Print_ISBN

0-7803-7614-5

Type

conf

DOI

10.1109/WSC.2002.1172894

Filename

1172894