[R-sig-Geo] geoR Beta Estimates Not Equal to lm Coefficients: Why?

[Edzer J. Pebesma]

Joshua,

My guess is that to estimate beta geoR uses generalized least squares 
and lm and SAS ordinary least squares. If you use a pure nugget model,  
or some other model with a range parameter sufficiently close to zero, 
i.e. model the observations as independent, the estimates should be the 
same.
--
Edzer

Joshua Palmer wrote:
> Hello everyone,
>
> I am using the excellent geoR package to perform Kriging with External
> Drift.  As to be expected, for any given set of covariates, trend
> coefficients I obtain performing least-squares regression in SAS equal those
> coefficients obtained by using R's lm function.  However, those trend
> coefficients do NOT match the estimates for the beta values when I run
> krige.conv (or likfit or variofit) in geoR.  The coefficients are often
> similar, but they are never nearly or exactly the same.  I was under the
> assumption that geoR utilizes least-squares regression (on the trend.d
> matrix) a la R's lm function to derive beta estimates.  This appears to be
> incorrect.
>
> Would anyone be able to explain to me why I am noting this difference or
> should I be noting a difference?  I have researched R mailing lists and geoR
> documentation but have been unable to find an answer.  Please let me know if
> additional specificity is needed.  This dilemma is universal across
> different sets of covariates and covariance models or parameters.
>
> Any assistance is greatly appreciated and I thank you for your time.
> Joshua Palmer
> Meteorologist
> Atlanta, GA, USA
>
> _______________________________________________
> R-sig-Geo mailing list
> R-sig-Geo at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>