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phantom NA/NaN/Inf in foreign function call (or something altogether different?)

2 messages · Cecile De Cat, R. Michael Weylandt

Cecile De Cat
# 
Dear experts,

Please forgive the puzzled title and the length of this message - I
thought it would be best to be as complete as possible and to show the
avenues I have explored.

I'm trying to fit a linear model to data with a binary dependent
variable (i.e. Target.ACC: accuracy of response) using lrm, and
thought I would start from the most complex model (of which
"sample1.lrm1" is a trimmed version).   I got the error shown below.
(sample1 is available at http://tinyurl.com/bwqq7ya)

For info:
'data.frame':   14022 obs. of  5 variables:
 $ Target.ACC : Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
 $ Word.Order : Factor w/ 2 levels "HeadMod*","ModHead": 1 1 1 1 1 1 1 1 1 1 ...
 $ Target.RESP: Factor w/ 2 levels "1","2": 2 2 2 2 2 2 2 2 2 2 ...
 $ L1         : Factor w/ 3 levels "English","German",..: 2 2 2 2 2 2
2 2 2 2 ...
 $ Relation   : Factor w/ 4 levels "For","From","MadeOf",..: 1 1 1 1 1
1 1 1 1 1 ...

Commands and error message:
Error in lrm(Target.ACC ~ (L1 + Relation + Target.RESP + Word.Order)^2,  :
  Unable to fit model using ?lrm.fit?

So I tried to narrow down the error by looking at all the combinations
manually, and the problem appears to be specifically with the
interaction between Word.Order and Target.RESP.  Models including
interaction of these variables with other variables (e.g. L1,
Relation) can be fitted without problem.
Error in lrm(Target.ACC ~ (Target.RESP + Word.Order)^2, dat, x = T, y = T) :
  Unable to fit model using ?lrm.fit?

unproblematic:
When running the problematic analysis on a smaller sample of the same
data, I get a different (more precise?) error message:
Error in fitter(X, Y, penalty.matrix = penalty.matrix, tol = tol,
weights = weights,  :
  NA/NaN/Inf in foreign function call (arg 1)

But I cannot find any NA in the data:
TRUE
 500

Some portions of the data don't appear to contain any of the offending "bit":
Could one of your shine your light on this puzzle, please? If that
includes pointing me towards some background reading, that would be
great too.

Many thanks in advance.

Cecile De Cat
Linguistics - University of Leeds
R. Michael Weylandt
#
On Tue, Jul 31, 2012 at 5:26 AM, Cecile De Cat <c.decat at leeds.ac.uk> wrote:
Not a complete answer, but complete.cases() won't pick up +/- Inf.

x <- data.frame(1:5, letters[1:5], c(NA, NaN, Inf, -Inf, 0))

x[complete.cases(x),]

You could perhaps use something like

sapply(x, is.finite)

with any()/all() to hunt them down (is.finite requires "real" numbers:
it gives false for NA, NaN, Inf, and -Inf).

Best,
Michael