Variance and Covariance Matrix D and R in nlme or lme4 part II [Please]
Alexandre Galv??o Patriota wrote:
Hi Douglas, I need to find the matrix V=ZDZ'+R, for example: require(nlme) data(Orthodont) attach(Orthodont) fm1 <- lme(distance ~ age + Sex, data = Orthodont,random=~age) X<-model.matrix(distance ~ age + Sex) Z<-model.matrix(distance ~ age + Subject -1) D<-diag(ncol(Z)) cova<-VarCorr(fm1,rdig=7) D[,1]<-D[1,]<-as.numeric(cova[2,3])*as.numeric(cova[1,2])*as.numeric(cova[2,2]) diag(D)<-c(as.numeric(cova[1,1]),rep(as.numeric(cova[2,1]), 27)) se2<-summary(fm1)$sigma^2 V<-Z%*%D%*%t(Z) + se2*diag(108) Is It right?? I compared a function vcov(fm1) with solve(t(X)%*%solve(V)%*%X). Could you give me a hint on why the two functions are giving incompatible results?
I don't know. I wouldn't calculate the variance-covariance matrix for the parameter estimates that way.