Let do a simple glm:
> y=rnorm(100)
> gnul <- glm(y ~ 1)
> gnul$coefficients
(Intercept)
0.1399966
The logLik shows the fit of two parameters (DF=2) (intercept) and sd
> logLik(gnul)
'log Lik.' -138.7902 (df=2)
But where is the sd term in the glm object?
If I do the same with optim, I can have its value
> dnormx <- function(x, data) {1E9*-sum(dnorm(data, mean=x["mean"],
sd=x["sd"], log = TRUE))}
> parg <- c(mean=0, sd=1)
> o0 <- optim(par = parg, fn=dnormx, data=y, method="BFGS")
> o0$value/1E9
[1] 138.7902
> o0$par
mean sd
0.1399966 0.9694405
But I would like have the value in the glm.
(and in the meantime, I don't understand why gnul$df.residual returned
99... for me it should be 98=100 - number of observations) -1 (for mean)
- 1 (for sd); but it is statistical question... I have asked it in
crossvalidated [no answer still] !)
Thanks
Marc
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