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+**Some Generalizations of Gneiting's Univariate and Bivariate Models**
+Prof. Dr. Martin Schlather
+Institut für Mathematik
+Universität Mannheim
+(joint work with Olga Moreva & NIklas Hansen)
+Gaussian random fields are completely characterized by their mean and
+their covariance function. In applications suitable classes
+of parametrized covariance functions are needed. Whilst in the
+univariate case a large number of classes is available, not that many
+classes exist in the multivariate case. In this talk we mainly focus
+on bivariate covariance functios that are generalizations or
+modifications of models that have been suggested by Tilmann Gneiting.
+In particular, the univariate cutoff embedding technique is transferred
+to the
+bivariate case. On that way, the results for the univariate case had
+to improved. As examples for the bivariate cutoff technique, we consider
+Gneiting's bivariate Matern model and modifications thereof.
+Finally, we show that Gneiting's generalized Cauchy model can be
+combined with the fractional Browian motion to get a parametric model
+that covers both the stationary and the intrinsically stationary case.

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