Hi,
If we know the residual of the model, how could we calculate the Log
likelihood?
It depends on the model (lm? glm? nls?). Why not using directly the
logLik function?
x <- rnorm(100, 10)
y <- rnorm(100, 10)
model1 <- lm(y ~ x)
logLik(model1)
model2 <- glm(y ~ x, family=gaussian)
logLik(model2)
model3 <- glm(y ~ x, family=Gamma)
logLik(model3)
Cheers,
Arnaud.
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