The number you need for MSE is
sum(residuals(model)^2)/df.residual(model)
On Wed, Sep 4, 2024 at 3:34 PM Daniel Lobo <danielobo9...@gmail.com> wrote:
>
> Hi,
>
> I am trying to replicate the R's result for VCV matrix of estimated
> coefficients from linear model as below
>
> data(mtcars)
> model <- lm(mpg~disp+hp, data=mtcars)
> model_summ <-summary(model)
> MSE = mean(model_summ$residuals^2)
> vcov(model)
>
> Now I want to calculate the same thing manually,
>
> library(dplyr)
> X = as.matrix(mtcars[, c('disp', 'hp')] %>% mutate(Intercept = 1));
> solve(t(X) %*% X) * MSE
>
> Unfortunately they do not match.
>
> Could you please help where I made mistake, if any.
>
> Thanks
>
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