[R] lm without error

Joris Meys jorismeys at gmail.com
Fri Jun 11 16:18:15 CEST 2010

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


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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