well Factorial Kriging Analysis allows you to tailor the filtering weights
to the spatial patterns in your data. You can use the same filter size but
different kriging weights depending on whether you want to estimate
the local or regional scales of variability.

Pierre

2010/2/1 seba <sebastiano.trevis...@libero.it>

>  Hi José
> Thank you for the interesting references. I'm going to give a look!
> Bye
> Sebastiano
>
>
>
> At 15.46 01/02/2010, José M. Blanco Moreno wrote:
>
> Hello again,
> I am not a mathematician, so I never worried too much on the theoretical
> reasons. You may be able to find some discussion on this subject in Eubank,
> R.L. 1999. Nonparametric Regression and Spline Smoothing, 2a ed. M. Dekker,
> New York.
> You may be also interested on searching information in and related to
> (perhaps citing) this work: Altman, N. 1990. Kernel smoothing of data with
> correlated errors. Journal of the American Statistical Association, 85:
> 749-759.
>
> En/na seba ha escrit:
>
> Hi José
> Thank you for your reply.
> Effectively I'm trying to figure out the theoretical reasons for their use.
> Bye
> Sebas
>
>


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