I'd like to create a variogram fit from some semivariance data in R.
I realize that a variogram fit requires an object generated by vgm, and raw.vgm gneerated by variogram, for example:
x = seq(0,300,by=300/100)
y = seq(0,0.9,by=(0.9/100))
Z = seq(0.0,10.0,by=(10/100))
raw.dat = data.frame(x=x,y=y,Z=Z)
g <- gstat(formula=Z~1, locations=~x+y, data=raw.dat)
raw.vgm <- variogram(g)
vg.exp <- vgm(psill=0.8,model='Exp', range = 50)
fit.exp <- fit.variogram(raw.vgm , model = vg.exp)
However, if I already have the gamma (semivariance) and distance values, how do I obtain a gstat object from that?
The following throws an error:
dist = seq(0,30,by=0.3)
gamma = seq(0,0.9,by=(0.9/100))
raw.vgm = data.frame(dist=dist,gamma=gamma)
vg.exp <- vgm(psill=0.8,model='Exp',range=20)
fit.exp <- fit.variogram(raw.vgm, model=vg.exp)
The error is the folowing:
Error in fit.variogram(raw.vgm, model = vg.exp) :
object should be of class gstatVariogram or variogramCloud
I only have the gamma and distance lags. how do I create a gstatVariogram or variogramCloud? thanks.
After creating raw.vgm, you have to set its class by
class(raw.vgm) = c("gstatVariogram", "data.frame")
then, fit.variogram also expects that a variogram has an np field, with the number of pairs of points used; I'm setting it to one by
raw.vgm$np = rep(1, nrow(raw.vgm))
and finally the default fit.method assumes you have no variogram values for distance zero, so you may want to try other values, like
fit.exp <- fit.variogram(raw.vgm, model=vg.exp,fit.method=1)