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singular model fit

3 messages · Javier Leon Patino, ONKELINX, Thierry, Tom Gottfried

Javier Leon Patino
# 
Dear list,

I am aware there are many post dealing with singular model variogram fits but I have not been able to fix my problem even after re-scaling the coordinates and variables.

I am using fit.variogram(gstat) on the file 'trans.csv' (attached) and have tried several values for the range, sill and nugget and different models. The following gives me an ok variogram (from visual plot) but still a 'singular model' warning.

library(sp)
library(gstat)
points <- read.csv("trans.csv")
coordinates(points)=~x+y
depth.ivgm <- vgm(model='Gau',range=1000, psill=var(points$ln_depth))
depth.vgm <- fit.variogram(variogram(ln_depth~x+y, points), model=depth.ivgm)

Any ideas on why I am getting a singular fit? Is it the small number of samples used?

Cheers,

Javier

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Tom Gottfried
# 
Hi Javier,

Am 15.09.2011 09:40, schrieb Javier Leon Patino:
you use the variance of ln_depth as an estimate for the sill here. Thus, I suspect you want the 
variogram of ln_depth.
What you calculate here with variogram() is a residual variogram of ln_depth from a first order 
trendsurface over your coordinates. Might that be the cause?

Tom