I found my problem:
The following function gave llGp1, llGp2 and ll22:
logLik_lm <- function(object){
res <- resid(object)
n <- length(res)
s2MLE <- sum(res^2)/n
lglk <- (-n/2)*(log(2*pi*s2MLE)+1)
lglk
}
logLik(fitGp1)
logLik(fitGp1)-logLik_lm(fitGp1)
llGp1 - logLik_lm(fitGp1)
Hello, all:
I have a dataset with 2 groups. I want to estimate 2 means and 2
standard deviations. I naively think I should be able to use lme to do
that, e.g., lme(y~gp, random=y~1|gp, method='ML'). I think I should get
the same answer as from lm(y~1, ...) within each level of group.
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