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 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 the R2 I compute using the
Removing the intercept can harm your sanity. See
http://markmail.org/message/q67jf7uaig7d4tkm
for an example.
Dieter
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