Flexible modelling of the covariance structure of univariate and
multivariate spatial processes 
Dr. Alexandra Schmidt
Instituto de Matemática – UFRJ, Brazil
Monday, March 19, 2007
4:10 p.m.
223 Weber
ABSTRACT
In geostatistics it is common practice to assume that the underlying spatial
process
is stationary and isotropic, that is the spatial distribution is unchanged
when the origin
of the index set is translated and the process is stationary under rotations
about the origin.
However in environmental problems, it is not very realistic to make such assumptions since local influences in the correlation structure of the
spatial process may be clearly found in the data.
On the other hand, when dealing with multivariate spatial processes, a
critical specification is its cross covariance function. It is common
practice to assume it is separable, which might not be a reasonable
assumption. In this talk I will describe some models which propose flexible
modelling of the covariance structure for univariate and multivariate
spatial processes.
