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seminarios:martin2018 [2018/11/26 20:41] (atual)
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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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