Dear R users! I used lme to fit a mixed model with random intercept and spatial Gaussian correlation i.e. I fitted a model of the following form:
Y = X*beta + error and error = U + W(t) + Z where U is the random intercept (normally distributed), W(t) the stationary Gaussian process and Z also a normally distributed (the residual) rv. Each of these three random variables have a variance which I am not sure to which output in lme they belong to. VarCorr gives the intercept and residual variance which I assume belong to U and Z respectively. The output of lme gives another estimate called "range" which I assume belongs to the parameter estimate needed for the Gaussian correlation. Are my assumptions correct? And where can I get the variance for the W(t) from? Thanks for any answers...and happy new year... Hadassa ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
