Introduction to kriging

Rodolphe Le Riche 1
1 DEMO
LIMOS - Laboratoire d'Informatique, de Modélisation et d'optimisation des Systèmes, DEMO-ENSMSE - Département Décision en Entreprise : Modélisation, Optimisation
Abstract : This is a two hours class on conditional Gaussian processes, i.e., kriging. We attempt to strike a compromise between a good theoretical foundation on Gaussian processes and practical issues (e.g., how to sample a Gaussian process). Note also that the case of Gaussian Processes with trends is discussed. Finally, we try to link kriging to Bayesian regression and Support Vector Machines. Illustrations are based on the R package DiceKriging.
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https://hal.archives-ouvertes.fr/cel-01081304
Contributor : Le Riche Rodolphe <>
Submitted on : Friday, November 7, 2014 - 2:45:06 PM
Last modification on : Tuesday, October 23, 2018 - 2:36:11 PM
Long-term archiving on : Sunday, February 8, 2015 - 10:41:26 AM

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  • HAL Id : cel-01081304, version 1

Citation

Rodolphe Le Riche. Introduction to kriging. Doctoral. France. 2014. ⟨cel-01081304⟩

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