[R-sig-Geo] Filtering out measurement error with krigeST
Andrew Zammit Mangion
azm at uow.edu.au
Tue Sep 8 15:47:31 CEST 2015
I wish to check whether I'm missing something obvious or whether what I need is still not implemented. I like to assume that my observations (Z) are different from my underlying process (Y) and that Z = Y + e. I also want to predict Y and and not Z.
I know there is a way to do this with krige(), namely by using a variogram defined with an Err() component instead of a Nug() component. That seems to work fine. For example if I do
library(gstat)
library(sp)
data(meuse)
coordinates(meuse) = ~x+y
data(meuse.grid)
gridded(meuse.grid) = ~x+y
m <- vgm(.59, "Sph", 874, .04)
x1 <- krige(log(zinc)~1, meuse, meuse.grid, model = m)
m <- vgm(.59, "Sph", 874, Err=.04)
x2 <- krige(log(zinc)~1, meuse, meuse.grid, model = m)
then the predictive variance of x1 and x2 are different as expected. However I don't see where I can define an Err() component when constructing a spatio-temporal variogram with vgmST (the help doesn't seem to indicate that this is possible). If I do specify and "Err" parameter in one or both of the space-time variograms (which is undoubtedly wrong, as this should be a parameter to the vgmST function if anything), no error is thrown, but the prediction variances from krigeST are unchanged, suggesting that predictions are still being carried out on Z and not on Y. Any ideas?
Thanks for your help,
Andrew
--
Andrew Zammit Mangion
School of Mathematics and Applied Statistics,
University of Wollongong, Australia
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