Adding constrained discontinuities to Gaussian process models of wind fields

Advances in Neural Information Processing Systems

Volumn , Issue , 1999, Pages 861-867

  Cornford, Dan ^a   Nabney, Ian T ^a   Williams, Christopher K I ^a,b  

^a ASTON UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

GAUSSIAN DISTRIBUTION;

BOUNDING SURFACES; GAUSSIAN PROCESS MODELS; GAUSSIAN PROCESSES; MCMC SAMPLING; MODEL PARAMETERS; MODELLING METHOD; NEAR-SURFACE WINDS; SPATIAL DATA;

GAUSSIAN NOISE (ELECTRONIC);

EID: 0012279519     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Cornford, D. 1998. Flexible Gaussian Process Wind Field Models. Technical Report NCRG/98/017, Neural Computing Research Group, Aston University, Aston Triangle, Birmingham, UK.
2. Cowles, M. K. and B. P. Carlin 1996. Markov-Chain Monte-Carlo Convergence Diagnostics-A Comparative Review. Journal of the American Statistical Association 91, 883-904.
3. Cressie, N. A. C. 1993. Statistics for Spatial Data. New York: John Wiley and Sons.
4. Daley, R. 1991. Atmospheric Data Analysis. Cambridge: Cambridge University Press.
5. Handcock, M. S. and J. R. Wallis 1994. An Approach to Statistical Spatio-Temporal Modelling of Meteorological Fields. Journal of the American Statistical Association 89, 368-378.
6. Neal, R. M. 1993. Probabilistic Inference Using Markov Chain Monte Carlo Methods. Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto. URL: http://www.cs.utoronto.ca/~radford.