[R-sig-Geo] Back-transformation of Beta in geoR

[Ruben Roa]

Hi:

I am interested in back-transforming the mle of parameter Beta
and its variance when the Lambda parameter of the Box-Cox 
transformation has been estimated and its estimate is not 0 nor 
0.5.
Is this back-transformation equivalent to simply averaging over
a fine grid inside the polygon containing the predictions of, say
krige.conv (given that geoR back-transform when kriging=
predicting)?
For example
>alpha<-sum(krig.object$pred)/N
>salpha<-sum(sqrt(krig.object$krige.var))/N
where krig.object has been obtained by using a likfit
object as argument in krige.control, and N is the number of nodes 
in the grid (a big number).
The questions are, 
1) is alpha aproximately equal to the back-
transformation of the mle of Beta?
2) is salpha aproximately equal to the 'standard
error' of the back-transformation of the mle of Beta?

Ruben