Dear Colleagues

The following arguement puzzling me. Your clarification will be greatly

appreciated.

When a random funtion Y(x) is not stationary, then one could prove the

relation between variogram and covarinace as:

2\gamma(x,x')=\sigma(x,x)+\sigma(x',x')+[m(x)-m(x')]^2-2\sigma(x,x')

I was hoping to derive the above relationship starting with the following

definition of variogram with no success.

2\gamma(x,x')=Var[Y(x)-Y(x')]^2

I was not able to reproduce the term [m(x)-m(x')]^2.

Am I missing something in this process?

Thanks

MJA

p.s. Most likely, my problem has something to do with misconception of

intrinsic hypothesis