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

[ONKELINX, Thierry]

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
read.

I think this will solve your problem.

HTH,

Thierry


------------------------------------------------------------------------
----
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
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx op inbo.be 
www.inbo.be 

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey

-----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 
predictor. 

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:

model<-glm(species~temp+prec+elev,family=binomial(link=logit))
#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 
(length=319)

wholearea<-data.frame(cbind(as.vector(temperature),as.vector
(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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