[R-sig-ME] corGaus specification

[ONKELINX, Thierry]

Dear Jennifer,

Have you tried to specify some staring values for the correlation. I
noticed that lme uses a fraction of the smallest distance between two
points as starting value for the range. Changing that value to a more
sensible one based a variogram yielded more realistic parameters for
range and nugget.

HTH,

Thierry

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Gaverstraat 4
9500 Geraardsbergen
Belgium

Research Institute for Nature and Forest
team Biometrics & Quality Assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium

tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey
  

> -----Oorspronkelijk bericht-----
> Van: r-sig-mixed-models-bounces at r-project.org 
> [mailto:r-sig-mixed-models-bounces at r-project.org] Namens jjclark
> Verzonden: dinsdag 8 juni 2010 21:22
> Aan: r-sig-mixed-models at r-project.org
> Onderwerp: [R-sig-ME] corGaus specification
> 
> 
> I'm trying to run a linear mixed model with a spatial 
> gaussian correlation using the lme function.  I have a y, a 
> linear term, x, and 5 additional variables (z1,z2,z3,z4,z5) 
> for each observation and am trying to build a model with a 
> random effect for each observation with the z variables used 
> in the gaussian correlation.  In SAS the following code 
> builds this model:
> proc mixed data=dat; 
> class obs; 	
> model y=x / ddfm=bw;	
> random obs/type=sp(gau)(z1 z2 z3 z4 z5); run;
> 
> I am still fairly new to using R and have tried using the 
> following code to build this same model with no success:
> 
> cobs=factor(obs)
> lme(y ~ x, dat, random = ~ 1|cobs, correlation = corGaus(form = ~
> z1+z2+z3+z4+z5|cobs))
> 
> The code runs when I take out the correlation specification, 
> but with it I get the following error:
> Error in corFactor.corSpatial(object) : NA/NaN/Inf in foreign 
> function call (arg 1) In addition: Warning messages:
> 1: no non-missing arguments to min; returning Inf in:
> min(unlist(attr(object, "covariate")))
> 2: no non-missing arguments to min; returning Inf in:
> min(unlist(attr(object, "covariate")))
> 
> All the z's are between 0 and 1 and are non-missing.  Can 
> anyone give me some pointers as to how to specify the 
> Gaussian spatial correlation for mixed models either here or 
> perhaps in another R function?  Thank You!
> 
> Jennifer
> 
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list 
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> 

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