[R] Coefficient of determination when intercept is zero
endeitz at yahoo.com
Thu Jan 18 06:53:12 CET 2007
Thanks for the guidance. With the help of your explanation, I was able to
find this reference that provides a good explanation of why the definition
may be different in the "no intercept" or "regression through origin" case.
For future readers of this list, the reference is:
Joseph G. Eisenhauer (2003)
Regression through the Origin
Teaching Statistics 25 (3), 76–80.
Prof Brian Ripley wrote:
> This is documented on ?summary.lm.
> It is not that 'intercept is zero' or 'zero intercept', it is that there
> is no intercept term in the model.
> On Wed, 17 Jan 2007, endeitz wrote:
>> I am curious as to the "lm" calculation of R2 (multiple coefficient of
>> determination, I assume) when intercept is zero. I have 18 data points,
>> independent variables:
>> First, a model with an intercept:
>>  0.6257541
>>  0.6257541
>> The $r.squared and the result from "cor" are the same, as I would expect.
>> Now we try a model with zero intercept:
>>  0.9099358
>>  0.5813659
>> Why has the $r.squared value increased to 0.9? And now the result from
>> "cor" is not the same? Is there a special way to calculate the
>> of determination when the intercept is zero?
> Brian D. Ripley, ripley at stats.ox.ac.uk
> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
> University of Oxford, Tel: +44 1865 272861 (self)
> 1 South Parks Road, +44 1865 272866 (PA)
> Oxford OX1 3TG, UK Fax: +44 1865 272595
> R-help at stat.math.ethz.ch mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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