Thanks for your response.
I actually tried to run the script you gave and got 1. I applied the same
concept to my data as
variogram(yield~1, canmod.sp,cutoff=1e6)$gamma
 and it equally give 1. the reason for not having one is because of the
the script I used as

empvar<-variogram(yield~1,canmod.sp, cutoff=300, width=5, cressie=TRUE)

where my variogram is based on the first 300 meter distance with lag
distance of 5. This is field data with irregular pattern. Is it a must to
define a lag tolerance?
Concerning my second question where I have nugget value of zero. Does it
implies that the exponential structure accounted for 100% of total
variation?


 model     psill    range
1   Nug 0.0000000  0.00000
2   Exp 0.8066099 11.36279


Thank you.
Moshood




On Wed, Dec 11, 2013 at 10:50 AM, Edzer Pebesma <
edzer.pebesma@uni-muenster.de> wrote:

> Try:
>
> library(sp)
> demo(meuse,ask=F)
> library(gstat)
> m = meuse$zinc
> meuse$m = (meuse$zinc - mean(meuse$zinc))/sd(meuse$zinc)
> var(meuse$m)
> # [1] 1
> variogram(m~1, meuse, cutoff=1e6)$gamma
> # [1] 1
>
> you see that the semivariogram averaged over ALL distances equals the
> variance of the variable. What you look at is (for good reasons) the
> semivariogram computed up to a certain distance.
>
> Hth,
>
> On 12/11/2013 06:17 PM, Moshood Agba Bakare wrote:
> > Dear All,
> > I used gstat package of R to fit variogram model to experimental
> variogram
> > having normalized the raw data as
> >
> > VN = (VP -VMean)/VSd
> >
> > Where VN is the normalized yield value, VP is the original yield value at
> > sampling point, VMean is average yield  value, and VSd is the standard
> > deviation of yield value.
> >
> > The reason for normalization is to be able to assess the stability of
> > spatial pattern of yield over a number of years. Having normalized the
> > data, I expected the sill i.e. the variance of the data to be one but to
> my
> > surprise the semivariogram plot shows sill of 0.8. What is responsible
> for
> > this?
> >
> > The result of fitting exponential function showed a nugget effect of zero
> > as showed below
> >
> > ## Exponential variogram model> exp.var<-vgm(psill = 0.8, model="Exp",
> > range= 15, nugget= 0.1)> exp.mod<-fit.variogram(empvar,model=exp.var)>
> > print(exp.mod)  model     psill    range
> > 1   Nug 0.0000000  0.00000
> > 2   Exp 0.8066099 11.36279
> >
> >
> > Does it mean the exponential structure explained 100 percent of total
> > variation in a normalized yield variable? I am confused! Have a look at
> the
> > attached file for the semivariogram plot. Do I need to detrend before
> > fitting the model? it seems the plot increases monotonically without
> level
> > off. Please advise.
> >
> > Thank you
> > Moshood
> >
>
> --
> Edzer Pebesma
> Institute for Geoinformatics (ifgi), University of Münster
> Heisenbergstraße 2, 48149 Münster, Germany. Phone: +49 251
> 83 33081 http://ifgi.uni-muenster.de GPG key ID 0xAC227795
>
>

	[[alternative HTML version deleted]]

