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Alternative sampling methods for estimating multivariate normal probabilities

Lookup NU author(s): Dr Peter Andras

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Abstract

We study the performance of alternative sampling methods for estimating multivariate normal probabilities through the GHK simulator. The sampling methods are randomized versions of some quasi-Monte Carlo samples (Halton, Niederreiter, Niederreiter-Xing sequences and lattice points) and some samples based on orthogonal arrays (Latin hypercube, orthogonal array and orthogonal array based Latin hypercube samples). In general, these samples turn out to have a better performance than Monte Carlo and antithetic Monte Carlo samples. Improvements over these are large for low-dimensional (4 and 10) cases and still significant for dimensions as large as 50. © 2003 Elsevier B.V. All rights reserved.

Publication metadata

Author(s): Sandor Z, Andras P

Publication type: Article

Publication status: Published

Journal: Journal of Econometrics

Year: 2004

Volume: 120

Issue: 2

Pages: 207-234

ISSN (print): 0304-4076

ISSN (electronic): 1872-6895

Publisher: Elsevier BV

URL: http://dx.doi.org/10.1016/S0304-4076(03)00212-4

DOI: 10.1016/S0304-4076(03)00212-4

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