Dear All,
Common variogram models were fitted to empirical variogram with the
following range of spatial dependency obtained.
*model *                 *range*
Spherical                14.2
Gaussian                   7.5
Exponential                5.5
Linear                       10.4

I intend to cross validate the models to determine the best that capture
the spatial pattern.I thought of defining *maxdist option *to be the value
of range so the the prediction can be done by the points within the range
of spatial dependency. Am I doing the right thing? Using range as maxdist,
will it give me a reliable RMSE and MSDR diagnostic statistics?

#### Cross validation of the variogram models by ordinary kriging
sph.kcv <- krige.cv(yield ~ 1, canmod.sp, model = sph.var,nmax = 100, nfold
= 5, *maxdist = 14.2*)
gau.kcv <- krige.cv(yield ~ 1, canmod.sp, model = gau.var,nmax = 100, nfold
= 5,* maxdist = 7.5*)exp.kcv <- krige.cv(yield ~ 1, canmod.sp, model =
exp.var,nmax = 100, nfold = 5, *maxdist = 5.5*)
  lin.kcv <- krige.cv(yield ~ 1, canmod.sp, model =    lin.var,nmax = 100,
nfold = 5, *maxdist=10.4*)


Look forward to your comment as usual. Thanks for the support.

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