On 27.06.2012 10:36, Christof Kluß wrote:
for example the same model with intercept R² = 0.6, without intercept R²
= 0.9 and higher. In my definition of R², R² has to be equal or less
without intercept
I do not know what R shows, but in the summary of the model without
intercept it does not show the R² of the regression line.
When I run a regression I like to have the R² of the regression line and
not something else. ;)
Ah, now I understand your question, see ?summary.lm:
r.squared: R^2, the ‘fraction of variance explained by the model’,
R^2 = 1 - Sum(R[i]^2) / Sum((y[i]- y*)^2),
where y* is the mean of y[i] if there is an intercept and
zero otherwise.
With your definition of R^2 you can use:
1 - crossprod(residuals(model)) / crossprod(y - mean(y))
while R uses:
1 - crossprod(residuals(model)) / crossprod(y - 0)
Best,
Uwe Ligges
Am 27-06-2012 10:25, schrieb Uwe Ligges:
On 27.06.2012 09:33, Christof Kluß wrote:
Hi
is there a command that calculates the correct adjusted R-squared, when
I work without intercept? (The R-squared from lm without intercept is
false.)
Then we need your definition of your version of "correct" - we know the
definition of your version of "false".
Best,
Uwe Ligges
Greetings
Chrsitof
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