Abstract
Original language | English |
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Place of Publication | Birmingham |
Publisher | Aston University |
Number of pages | 16 |
ISBN (Print) | NCRG/98/020 |
Publication status | Published - 1998 |
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Keywords
- polynomial-exponential covariance function
- Gaussian process
- local wind vector
- multi-variate
Cite this
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Non-zero mean Gaussian process prior wind field models. / Cornford, Dan.
Birmingham : Aston University, 1998.Research output: Working paper › Technical report
TY - UNPB
T1 - Non-zero mean Gaussian process prior wind field models
AU - Cornford, Dan
PY - 1998
Y1 - 1998
N2 - This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.
AB - This report outlines the derivation and application of a non-zero mean, polynomial-exponential covariance function based Gaussian process which forms the prior wind field model used in 'autonomous' disambiguation. It is principally used since the non-zero mean permits the computation of realistic local wind vector prior probabilities which are required when applying the scaled-likelihood trick, as the marginals of the full wind field prior. As the full prior is multi-variate normal, these marginals are very simple to compute.
KW - polynomial-exponential covariance function
KW - Gaussian process
KW - local wind vector
KW - multi-variate
M3 - Technical report
SN - NCRG/98/020
BT - Non-zero mean Gaussian process prior wind field models
PB - Aston University
CY - Birmingham
ER -