[R] GAM, GLM, Logit, infinite or missing values in 'x'

[Simon Wood]

Anders,

A very flexible logistic regression model is quite often able to predict some 
subset of the data `perfectly' with the unfurtunate consequence that the 
corresponding linear predictor is not well defined. My guess would be that 
the extra flexibility of the gam is what is causing slightly more trouble 
with `gam' than with `glm'. 

That said the  `gam' fitting methods are supposed to deal with the numerical 
consequences of such indefiniteness more elegantly than is the case for your 
example. Any chance that you could send me the data so that I can dig into 
this a bit more, and see if whatever is causing the error could be dealt with 
more gracefully (or at least trapped earlier)? [If so, a text file usually 
seems most painless, and I of course undertake not to do anything with the 
data except investigate this issue].

best,
Simon

On Tuesday 08 January 2008 06:35, Anders Schwartz Corr wrote:
> Hi,
>
> I'm running gam (mgcv version 1.3-29) and glm (logit) (stats R 2.61) on
> the same models/data, and I got error messages for the gam() model and
> warnings for the glm() model.
>
> R-help suggested that the glm() warning messages are due to the model
> perfectly predicting binary output. Perhaps the model overfits the data? I
> inspected my data and it was not immediately obvious to me (though I guess
> it will be to some of the more pointed of you) how this would be the case.
>
> The gam() errors vanish when I delete one covariate (it doesn't matter
> which one). Can I write a loop into the code such that if an error is
> returned (is.error() doesn't seem to exist unfortunately) then I pare off
> one of the covariates and rerun the gam()? That would be ideal. I could
> set options(error = f()) in which f() reruns the gam with
> one fewer covariate until it works, but the gam is in a bunch of loops
> that would break given the error and I would like to figure out another
> option.
>
> My glm and gam models are below. Any suggestions are very much
> appreciated.
>
> Best,
>
> Anders
>
> > form.logit
>
> outbinary ~ a_norm_total2 + I(a_norm_total2^2) + prop + igoprop +
>      gpconc + ter + open + igototal + cinc.nmc + demsOnumstat +
>      diversity + cincOter + polity2
>
> > form.glogit
>
> outbinary ~ s(a_norm_total2) + s(prop) + s(prop, by = a_norm_total2) +
>      igoprop + gpconc + ter + open + igototal + cinc.nmc + demsOnumstat +
>      diversity + cincOter + polity2
>
> GAM error message:
> avt.2glogit<-gam(form.glogit, data=dataS,
> na.action=na.omit,family=binomial) Error in eigen(hess1, symmetric = TRUE)
> :
>    infinite or missing values in 'x'
> Calls: gam -> gam.outer -> newton -> eigen
>
> GLM warnings:
> There were 29 warnings (use warnings() to see them)
>
> > warnings()
>
> Warning messages:
> 1: In glm.fit(x = X, y = Y, weights = weights, start = start,  ... :
>    fitted probabilities numerically 0 or 1 occurred
> 2: In glm.fit(x = X, y = Y, weights = weights, start = start,  ... :
>    fitted probabilities numerically 0 or 1 occurred
> 3: In glm.fit(x = X, y = Y, weights = weights, start = start,  ... :
>    fitted probabilities numerically 0 or 1 occurred
> 4: In glm.fit(x = X, y = Y, weights = weights, start = start,  ... :
>    fitted probabilities numerically 0 or 1 occurred
>
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-- 
> Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK
> +44 1225 386603  www.maths.bath.ac.uk/~sw283