3 citations · 10 across the 5 of their papers we have counts for
Showing 2014Show all
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stat.ME2014★ 1 cited
Spatial composite likelihood inference using local C-vines
Tobias Michael Erhardt, Claudia Czado, Ulf Schepsmeier
We present a vine copula based composite likelihood approach to model spatial dependencies, which allows to perform prediction at arbitrary locations. This approach combines establ…
stat.ME2014★ 2 cited
R-vine Models for Spatial Time Series with an Application to Daily Mean Temperature
Tobias Michael Erhardt, Claudia Czado, Ulf Schepsmeier
We introduce an extension of R-vine copula models for the purpose of spatial dependency modeling and model based prediction at unobserved locations. The newly derived spatial R-vin…