geoR Beta Estimates Not Equal to lm Coefficients: Why?
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
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