Spatial Interpolation and Prediction of Gaussian and Max-Stable Processes

Räumliche Interpolation und Vorhersage von Gaußschen und max-stabilen Prozessen

by Marco Oesting
Doctoral thesis
Date of Examination:2012-05-03
Date of issue:2012-07-04
Advisor:Prof. Dr. Martin Schlather
Referee:Prof. Dr. Martin Schlather
Referee:Prof. Dr. Robert Schaback
Persistent Address: http://dx.doi.org/10.53846/goediss-2578

 

 

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Abstract

English

This thesis deals with different aspects of spatial interpolation and prediction of random fields. In the case of Gaussian random fields, best linear predictors and conditional distributions are well-known, provided that the mean and covariance structure of the random field are given. For parametric estimation of the covariance function from data, we consider the flexible class of Whittle-Mat
Keywords: Spatial Interpolation; Geostatistics; Reproducing Kernel Hilbert Spaces; Conditional Sampling; Max-Stable Processes; Brown-Resnick Processes
Schlagwörter: Räumliche Interpolation; Geostatistik; Bedingte Simulation; Max-stabile Prozesse; Brown-Resnick-Prozesse
 
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