Space-time statistics STAT 518 Sp08

Space-time processes Separable covariance structure: Cov(Z(x,t),Z(y,s))=C 1 (x,y)C 2 (s,t) Nonseparable alternatives Temporally varying spatial covariances Fourier approach Completely monotone functions

SARMAP study Spatial correlation structure depends on hour of the day (non-separable):

A national health effects study

Trend model where V ik are covariates, such as population density, proximity to roads, local topography, etc. where the f j are smoothed versions of temporal singular vectors (EOFs) of the TxN data matrix. We will set  1 (s i ) =  0 (s i ) for now.

SVD computation

EOF 1

EOF 2

EOF 3

Kriging of  0

Kriging of  2

Quality of trend fits

Observed vs. predicted