Zero nugget, but still residuals in cross-validation ?

Discussion created by lmthomsen on Jan 28, 2013
Latest reply on Jan 29, 2013 by lmthomsen
In my present project I am using ordinary kriging and comparing various models. I let the program decide on the nugget, it is set to TRUE and the measurement error model is set to 100%. Then it happens that the program comes up with a kriging-model where the nugget says zero, fx: Model : 0*Nugget+19742*Stable(154.68,1.3197)

but when I further in the wizard arrives at the Cross-validation, there is still prediction errors present. As I understood it, when the chosen model has a nugget of zero, the model will be an exact interpolator and so there should be no difference between the measured values and the predicted? Can someone please help me understanding this?

Best regards

L. Thomsen