[R-sig-Geo] Doubts about kriging
Ashton Shortridge
ashton at msu.edu
Thu Oct 2 15:25:09 CEST 2008
On Thursday 02 October 2008, GEMA FERNANDEZ-AVILES CALDERON wrote:
> Dear list,
>
> I have two problem and I would like to know you opinion.
>
> 1. I am kriging 6 environmental variables, SO2, NOx, O3, CO, NO, PM10, to
> built and enviromental index in R. I have standardized the observed values
> and I am implementing in geoR the function likfit to obtain the parameter
> lambda (Box-Cox transformation) to see if the standarized variables are
> normal. But I have error using the likfit function. It could be that the
> error arise because the standarized variables contain negative values?
>
> 2. I have values of the 6 variables at 25 locations but I want to use a
> linear combination of the six variables to deal with only a variable.
> Finally, I want to interpolate this only variable in several sites where I
> have not observed data. What do you think is better?
> - To interpolate each one of the six variables and then elaborate the
> linear combination. - Or to elaborate a linear combination with the
> observed values and finally krige the linear combination.
>
> Thanks in advance,
> Gema Fernández-Avilés
>
> Universidad de Castilla-La Mancha.
> (Spain)
>
>
> [[alternative HTML version deleted]]
Hi,
Dodging your questions a bit, but I have some concerns and/or issues for your
consideration:
1. 25 locations is very small for kriging, unless you have some other means to
develop your spatial covariance models. Perhaps you mean that the 6 variables
are collocated at only 25 locations, but you have other sites with fewer than
all 6? If not - if all you have are 25 sites with six variables each - I
wouldn't attempt kriging in any form.
2. Actually I think 25 is pretty small for the multivariate analysis you
propose as well.
3. With respect to your point 2, I would develop the linear combination with
the real data, not on a bunch of interpolated 'data'. Standard methods of
combining the variables will assume that the observations are independent; if
they aren't then the model will be flawed, so be cautious of that.
Hope this helps,
Ashton
--
Ashton Shortridge
Associate Professor ashton at msu.edu
Dept of Geography http://www.msu.edu/~ashton
235 Geography Building ph (517) 432-3561
Michigan State University fx (517) 432-1671
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