On Wed, 1 Dec 2010, Anna Berthinussen wrote:
Hi,
I receive the following warning message when I run a poisson GLM in R:
"glm.fit: fitted rates numerically 0 occurred"
The model summary is shown below. The variable 'Species' consists of
counts of different species ranging from 0 to 4. I suspect this may
have something to do with the warning message but I'm not sure. Can
anybody help?
This is a log-linear model, so that is saying that for at least one
observation the fitted value is very close to zero (and hence the
linear prediction is near -Inf: a lp around -30 gives small enough
fitted rates.).
This normally indicates some sort of separation in the data -- see
below for a suggestion of where to look.
Thank you!
Anna
Call:
glm(formula = Species ~ Dist + Time + Alt + Elev.road + Noise +
Cloud + Temp + Wind.sp + Water + Hab + Crossing, family = poisson,
data = bats1)
Deviance Residuals:
Min 1Q Median 3Q Max
-2.131083 -0.734566 0.005422 0.548956 2.186938
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -7.496e-01 6.642e-01 -1.128 0.25911
Dist 1.993e-04 1.233e-04 1.617 0.10593
Time -4.753e-04 2.114e-03 -0.225 0.82206
Alt 2.042e-04 1.265e-03 0.161 0.87180
Elev.road 2.189e-03 1.960e-03 1.117 0.26418
Noise -8.126e+01 4.528e+01 -1.795 0.07268 .
What is 'Noise'? Is a coefficient of -81 reasonable? Do all obs with
non-zero noise have observation = 0? That's the usual cause.
Cloud -1.059e-03 2.274e-03 -0.466 0.64150
Temp 6.660e-02 4.051e-02 1.644 0.10017
Wind.sp -7.553e-02 2.420e-02 -3.121 0.00180 **
WaterY -6.919e-02 1.744e-01 -0.397 0.69162
Hab 1.200e-01 5.051e-02 2.375 0.01755 *
CrossingUnd 9.496e-02 1.214e-01 0.782 0.43420
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 253.49 on 239 degrees of freedom
Residual deviance: 206.59 on 228 degrees of freedom
AIC: 681.56
Number of Fisher Scoring iterations: 6
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--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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and provide commented, minimal, self-contained, reproducible code.