Variogram Error
Saman, Ben Graeler managed to reproduce the same effect by: library(gstat) data(meuse) coordinates(meuse) <- ~x+y obj = gstat(NULL, "D1", zinc~1, meuse[1,], set = list(zero_dist = 3)) obj = gstat(obj, "D2", zinc~1, meuse[2,]) variogram(obj, cross = "ONLY", pseudo = T, boundaries=c(0,100)) Essentially, for ST variograms, for each time slice the mean was removed before computing the (pseudo) cross variogram. This will usually have little effect, unless you have very few, or as in this (and your) case, only one observation per time slice. We changed the code now such that the mean is not removed. Updates are committed r-forge; the next version on CRAN will include this update.
On 04/14/2013 06:10 PM, Saman Monfared wrote:
Hi,
I am trying to fit a st variogram .The values of variogram$gamma
in all st lags are 0. I don't no why this occurs!
Data is attached.
my program is:
rm(list=ls())
library(gstat)
library(spacetime)
library(maptools)
library(RColorBrewer)
library(maps)
library(lattice)
data<-read.table("cancer.rate.txt",header=TRUE)
cancer.loc<-read.table("bladder.loc.txt",header=TRUE)
pts<-cbind(cancer.loc$x,cancer.loc$y)
pts = SpatialPoints(pts)
data$time = ISOdate(data$year, data$mounth, data$day)
ind<-as.matrix(cbind(data$indexs,data$indext))
xx = STSDF(pts,data$time,data,ind)
vv<-variogram(Rate~1,xx,width=200000,cutoff=3000000,tlags=1:8)
plot(vv,map=T)
wireframe(gamma~spacelag+timelag,vv,col="red",drape=T,outer =T,
scales=list(arrows=FALSE))
separableModel<-vgmST("separable",space=vgm(.05,"Gau",10000, 0.1),
time =vgm(.02,"Gau", 100, 0),sill=.2,nugget=0)
v.f<-fit.StVariogram(vv,separableModel,method="L-BFGS-B")
v.f
wireframe(model~spacelag+timelag,variogramSurface(v.f,vv),drape=T,
aspect = c(1,1),panel.aspect =1,scales=list(arrows=F))
plot(vv,v.f)
grd<-read.table("farsgrid.txt",header=T)
grd = SpatialPixels(SpatialPoints(cbind(grd$x,grd$y)))
plot(grd)
n =3
library(xts)
tgrd = seq(max(index(xx)+31622400*2),max(index(xx)+3*31622400),length=2)
pred.grd = STF(grd, tgrd)
plot(pred.grd )
cancer.ST = krigeST(Rate~1,xx,pred.grd ,separableModel)
stplot(cancer.ST)
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