[R] Where is the SD in output of glm with Gaussian distribution

Eric Berger er|cjberger @end|ng |rom gm@||@com
Mon Dec 9 16:34:20 CET 2019

```summary(gnul)

shows the std error of the coefficient estimate

On Mon, Dec 9, 2019 at 5:16 PM Marc Girondot via R-help
<r-help using r-project.org> wrote:
>
> 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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