Dear R users, I'm estimating a mixed effects model in which the spatial correlation is controlled for by the "corGaus" structure. I'm wondering if there is a document or paper that explains how the spatial correlation structure (such as "corExp" or "corGaus") works.
Let me use the example and data posted on UCLA's R FAQ webpage to explain my problems. The link for the webpage is: http://www.ats.ucla.edu/stat/r/faq/spatial_regression.htm install.packages("nlme") library(nlme) spdata <- read.table("http://www.ats.ucla.edu/stat/R/faq/thick.csv";, header = T, sep = ",") dummy <- rep(1, 75) spdata <- cbind(spdata, dummy) ### estimate the null model ### soil.model <- lme(fixed = thick ~ soil, data = spdata, random = ~ 1 | dummy, method = "ML") summary(soil.model) plot(Variogram(soil.model,form=~north+east)) ### updated the model by the spatial correlation structure #### soil.gaus <- update(soil.model, correlation=corGaus(1,form=~north+east)) summary(soil.gaus) plot(Variogram(soil.gaus,form=~north+east)) My questions are: 1) Is there a way that I can tell, to what extent the spatial correlation has been controlled for by the model, besides the improvements of AIC, BIC, and Loglik? 2) where can I find the formulas for the corExp or corGaus? Thanks! Gary [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
