[R] lm without error

[ivo welch]

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)