Hi all,

I am using cokriging options for interpolating two datasets(A & B) in arcmap 10.1. I have first kept A in datasets 1# and B in datasets 2#. I got 0.8461 as the root mean square prediction error(rmspe). However, when I changed the order i.e, tried B in datasets 1# and A in datasets 2#, the rmspe increased to 3.6321. My doubt is that when we change the order , does it assign different weightage to the dataset which results in different rmspe?

I searched it on ESRI blogs but didn't get any solution.

Kindly help me with this.

Cokriging will actually interpolate the first variable you provide, but it will use information from the secondary dataset. The RMS prediction error is in the units of the first dataset, so if one variable generally has larger values and more variance than the other dataset, you would expect the RMS to be higher (all else being equal).

For example, if you have elevation data in feet and you get an RMS of 3, this means that, on average, the predictions will be off by about 3 feet. If your data is in yards, an RMS of 1 would indicate that your predictions will be off by about 1 yard on average. But since one yard is equal to 3 feet, these two models are equally accurate (all else being equal).

You should only expect the RMS values to be the same when switching primary and secondary variables if the two datasets are measuring the same thing in the same units and they have similar spatial configurations (ie, roughly the same number of points in the same general locations).