[R] lm without error

[Joris Meys]

Obvious solution : check your data before you throw it in the lm. lm()
shouldn't work in that situation, and if it would, I'd no longer use
R.

Cheers
Joris

On Fri, Jun 11, 2010 at 2:49 PM, ivo welch <ivowel at gmail.com> wrote:
> this is not an important question, but I wonder why lm returns an
> error, and whether this can be shut off.  it would seem to me that
> returning NA's would make more sense in some cases---after all, the
> problem is clearly that coefficients cannot be computed.
>
> I know that I can trap the lm.fit() error---although I have always
> found this to be quite inconvenient---and this is easy if I have only
> one regression in my lm() statement.
>
> but, let's presume I have a matrix with a few thousand dependent y
> variables (and the same independent X variables).  Let's presume one
> of the y variables contains only NA's.  I believe I now cannot use
> lm(y ~ X), because one of the regressions will throw the lm.fit
> exception.  (all the other y vectors should have worked.)
>
> or is there a way to get lm() to work in such situations?
>
> /iaw
>
> ----
> Ivo Welch (ivo.welch at brown.edu, ivo.welch at gmail.com)
>
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-- 
Joris Meys
Statistical consultant

Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control

tel : +32 9 264 59 87
Joris.Meys at Ugent.be
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