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Numerical evaluation of multinormal expectations

Brodtkorb, Per Andreas LU (2004) In Preprint without journal information
Abstract
The numerical computation of expectations for (nearly) singular multivariate normal distribution is a difficult problem, which frequently occurs in widely varying statistical contexts. In this article we discuss several strategies to improve the algorithm proposed by Genz and Kwong (2000) when either a moderate accuracy is requested, the correlation structure is strong, and, most importantly, the dimension of the integral is large. Test results for typical problems show an average speedup of 10 using the modified algorithm, but even more is gained as the dimension of the problem increases.

We apply the modified algorithm to compute long-run distributions of Gaussian wave characteristics, a difficult problem where previous... (More)
The numerical computation of expectations for (nearly) singular multivariate normal distribution is a difficult problem, which frequently occurs in widely varying statistical contexts. In this article we discuss several strategies to improve the algorithm proposed by Genz and Kwong (2000) when either a moderate accuracy is requested, the correlation structure is strong, and, most importantly, the dimension of the integral is large. Test results for typical problems show an average speedup of 10 using the modified algorithm, but even more is gained as the dimension of the problem increases.

We apply the modified algorithm to compute long-run distributions of Gaussian wave characteristics, a difficult problem where previous algorithms fail to compute accurate values in reasonable time. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
unpublished
subject
in
Preprint without journal information
issue
2004:29
publisher
Manne Siegbahn Institute
ISSN
0348-7911
language
English
LU publication?
yes
id
d4667fc5-92f8-4be2-aeb7-ff747a6ccaf3 (old id 929289)
date added to LUP
2008-01-14 16:04:15
date last changed
2016-04-16 06:32:50
@article{d4667fc5-92f8-4be2-aeb7-ff747a6ccaf3,
  abstract     = {The numerical computation of expectations for (nearly) singular multivariate normal distribution is a difficult problem, which frequently occurs in widely varying statistical contexts. In this article we discuss several strategies to improve the algorithm proposed by Genz and Kwong (2000) when either a moderate accuracy is requested, the correlation structure is strong, and, most importantly, the dimension of the integral is large. Test results for typical problems show an average speedup of 10 using the modified algorithm, but even more is gained as the dimension of the problem increases. <br/><br>
We apply the modified algorithm to compute long-run distributions of Gaussian wave characteristics, a difficult problem where previous algorithms fail to compute accurate values in reasonable time.},
  author       = {Brodtkorb, Per Andreas},
  issn         = {0348-7911},
  language     = {eng},
  number       = {2004:29},
  publisher    = {Manne Siegbahn Institute},
  series       = {Preprint without journal information},
  title        = {Numerical evaluation of multinormal expectations},
  year         = {2004},
}