User: Guest  Login
Document type:
Zeitschriftenaufsatz 
Author(s):
Erhardt, T.M., Czado, C. and Schepsmeier, U. 
Title:
Spatial composite likelihood inference using local C-vines 
Abstract:
We present a vine copula based composite likelihood approach to model spatial dependencies, which allows to perform prediction at arbitrary locations. It combines established methods to model (spatial) dependencies. On the one hand spatial differences between the variable locations are utilized to model the degree of spatial dependence. On the other hand the flexible class of C-vine copulas are used to model the spatial dependency structure locally. These local C-vine copulas are parametrized jo...    »
 
Keywords:
Daily mean temperature; Local dependency modeling; Non-Gaussian dependencies; Spatial R-vine model; Spatial statistics; Vine copulas 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Journal of Multivariate Analysis 
Year:
2015 
Journal volume:
138 
Pages contribution:
74-88 
Reviewed:
ja 
Language:
en 
Status:
Verlagsversion / published