### Abstract

Original language | English |
---|---|

Place of Publication | Birmingham |

Publisher | Aston University |

Number of pages | 16 |

ISBN (Print) | NCRG/98/020 |

Publication status | Published - 1998 |

### Fingerprint

### Keywords

- polynomial-exponential covariance function
- Gaussian process
- local wind vector
- multi-variate

### Cite this

*Non-zero mean Gaussian process prior wind field models*. Birmingham: Aston University.

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**Non-zero mean Gaussian process prior wind field models.** / Cornford, Dan.

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 -