Dear list,
It's never happened to me before in such a simple exercise but is not going
away and I've checked my data are good. I want a simple lm model with one
response and one predictor, where N is about 4,200 * data set not exactly
small. Both x and y are nice, continuous variables having NA filtered out with
a call to na.omit. So I did
mod = lm( y ~ x, data=x1)
Then the error,
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :
NA/NaN/Inf in foreign function call (arg 4)
I did a trace back and it turned out it's an error thrown by the Fortran
subroutine that seems to be trying a QR decomposition,
traceback()
3: .Fortran("dqrls", qr = x, n = n, p = p, y = y, ny = ny, tol =
as.double(tol),
coefficients = mat.or.vec(p, ny), residuals = y, effects = y,
rank = integer(1), pivot = 1:p, qraux = double(p), work = double(2 *
p), PACKAGE = "base")
2: lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...)
1: lm(log.p.sales ~ log.mktcap, data = x1)
My question is why would QR fail since the default in lm.fit is 'singular.ok' ?
Furthermore, is there a way to get around presumably a singularity in my design
matrix?
Thanks in advance.
Horace W. Tso
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