On Sun, Jun 28, 2009 at 3:38 AM, Dieter
Mennedieter.me...@menne-biomed.de wrote:
It seems odd to me that dropping the intercept
would cause the R^2 and F stats to rise so dramatically, and the p
value to consequently drop so much. In my implementation, I get the
same beta1 and beta2, and
On Mon, 29 Jun 2009, John Hunter wrote:
But my question was more numerical: in particular, the R^2 of the
model should be equal to the square of the correlation between the fit
values and the actual values.
No.
It is with the intercept and is not w/o
it, as my code example shows. Am I
I am writing some software to do multiple regression and am using r to
benchmark the results. The results are squaring up nicely for the
with-intercept case but not for the no-intercept case. I am not
sure what R is doing to get the statistics for the 0 intercept case.
...
It seems odd to me
I am writing some software to do multiple regression and am using r to
benchmark the results. The results are squaring up nicely for the
with-intercept case but not for the no-intercept case. I am not
sure what R is doing to get the statistics for the 0 intercept case.
For example, I would
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