[R] apply model predictions over larger area with predict()

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Wed Oct 15 09:57:29 CEST 2008

Dear Katrin,

Store the "old" data in a dataframe instead of vectors and supply the
name of that dataframe to your model. eg  
Model <- glm(species ~ temp + prec + elev, data = your.data.frame,
family = binomial(link = logit))

Notice that I've added some spaces which makes your code more easy to

I think this will solve your problem.



ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
tel. + 32 54/436 185
Thierry.Onkelinx op inbo.be 

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say what the experiment died of.
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-----Oorspronkelijk bericht-----
Van: r-help-bounces op r-project.org [mailto:r-help-bounces op r-project.org]
Namens K. Fleischer
Verzonden: woensdag 15 oktober 2008 9:34
Aan: r-help op r-project.org
Onderwerp: [R] apply model predictions over larger area with predict()

Dear all,

I have built glm models based on presences/absences and a number of 
predictor maps and would like to compute habitat suitability based on 
the modelled coefficients. 

I thought this is pretty straight forward and wanted to use predict() 
and supply the new data in a data frame, with one column for each 

However, I do get an error msg warning me that the number of rows for 
old and new data do not match. 

the script looks like that:

#whereby temp,prec,elev are in vector format and contain the elements 
on species presence/absence; species is vector of 0's and 1's 

(precipitation),as.vector(elevation))  # (length=7526)

predict(model, newdata=wholearea,type="response")

Warning message: 'newdata' had 7526 rows but variable(s) found have 
319 rows.

Ive searched quite a while for the answer now, has anyone encountered 
that problem before?? thanx in advance.

Katrin Fleischer
MSc Student 
Computational Geo-ecology
University of Amsterdam

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