[R] problem with gls : combining weights and correlation structure

From: <ybas_at_ens-lyon.fr>
Date: Tue 17 May 2005 - 23:16:45 EST

Dear R-users,

I hope you will have time to read me and I will try to be brief. I am also sorry for my poor english.

I used gls function from the package nlme to correct two types of bias in my database. At first, because my replicates are spatially aggregated, I would like to fit a corStruct function like corLin, corSpher, corRatio, corExp or corGaus in my gls model, and simultaneously, because my response variable is an estimate, I would like to use weights to take into account the accuracy of the estimation. I used a varFixed object corresponding to squared standard error.
Variograms all shows a weak but real spatial autocorrelation (nugget ~ 0.9 but they always increase with distance).
My first problem was the estimation of the parameters of the corStruc function which were very far from their order of magnitude (range > 10E15, though the

maximum distance between observations is no more than 10E6). I thought I had convergence problem that I could solve :
- with at first fitting corStruct functions to variograms with the solver of
- and secondly binding corStruct parameters to the obtained value with the
argument "fixed=TRUE"
But I obtained very unrealistic values for the parameters of the model even when the spatial autocorrelation was weak, so I am sure that the model fitting didn't work properly.
I had absolutely no problems in using the "corr" or the "weight" arguments

I thank you very much to read me and if you have a solution to my problem or if you know where I did a mistake, you would be very nice to answer me.

Sincerely yours,

Yves Bas

R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue May 17 23:22:23 2005

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