Hi Everyone,
I am very much suspicious of the result I obtained by looking at the
correlation coefficient of interpolated values from ordinary kriging,
inverse distance weighting with power of 1 and 2. My worry is that ordinary
kriging is highly correlated with other two methods knowing that former
integrates the spatial model in interpolation.
 Or may be looking at the correlation of interpolated values among the
methods is not the best. It would have been better looking at the
correlation of interpolated values from each method with the actual values
from the grid cell but the actual values are unknown.

The reason for not having the observed values in each cell is that the
original spatial data is irregularly space while the interpolation grid is
regular. This means I only have the interpolated value. The cross
validation of each interpolation method is difficult. Any assistance or
advice on how to approach this problem

See the correlation below

          krig.pred idw1.pred idw2.pred
krig.pred 1.0000000 0.9707277 0.9841281
idw1.pred 0.9707277 1.0000000 0.9844669
idw2.pred 0.9841281 0.9844669 1.0000000

#### Ordinary kriging to create kriging prediction object

orkrig <- krige(yield ~ 1, canmod.sp, newdata = grid,
model=exp.mod,nmax=20,maxdist=16.5)

## Inverse Distance Weighting (IDW) Interpolation method
idw1 = idw(yield~1, canmod.sp, newdata=grid,nmax=20,maxdist=16.5,idp=1)

idw2 = idw(yield~1, canmod.sp, newdata=grid,nmax=20,maxdist=16.5,idp=2)

Thank you
Moshood

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