[R] cv.glm function error message in a loop

[Prof Brian Ripley]

Please study the help page for cv.glm.  You have not specified `data' 
correctly in the loop case.  The help page says

Arguments:

     data: A matrix or data frame containing the data.  The rows should
           be cases and the columns correspond to variables, one of
           which is the response.

   glmfit: An object of class '"glm"' containing the results of a
           generalized linear model fitted to 'data'.
                                    ^^^^^^^^^^^^^^^^ 
and that is not what you specified.

On Thu, 16 Feb 2006, Maria Beger wrote:

> Dear list,
> I am modelling fish distributions using the glm-function followed by the
> step-function, and then want to cross-validate the model via the
> cv.glm-function from the {boot} package. I am working on fish
> distributions on coral reefs.  The code I have works for one fish
> species. Since I have 227 fishes, I wrote a loop.  Now the
> cv.glm-function comes up with an error message: "Error in
> model.frame(formula, rownames, variables, varnames, extras, extranames,
> : variable lengths differ" and I cannot work out what the problem is.
> All the data are the same length and I double-checked all.  I think its
> to do with how cv.glm addresses the fish data columns for the
> crossvalidation within "data".
>
> Any help would be appreciated, the code is below.  I can send more
> detail if required.
>
> Thank you very much for your help!!!  Maria
>
>
>
> "data" is a dataframe with the first 227 columns with fish
> presence/absence data (=response), then 10 columns of predictor
> variables.
>
> Code that doesn't work:
>
> for (i in 1:length(datafish))  #this is 227 columns within "data"
> {
> #run glm & step of fish.[i] with all parameters no interactions
> modelfish<-glm(data[,i]~ECO.NAME+ISLAND+DISTANCE.EST+DEPTH500M,
> binomial)
> stepmodfi<-step(modelfish,trace=1,scope=list(lower= ~1,
> upper=~ECO.NAME+ISLAND+DISTANCE.EST+DEPTH500M) ,direction="both")
> #run cross-validation
> fish.vali<-cv.glm(data,stepmodfi)
> }
>
> Code for one fish that works:
> modelfish.355<-glm(fi355~ECO.NAME+ISLAND+DISTANCE.EST+DEPTH500M,
> binomial, data=data)
> stepmodfi.355<-step(modelfish.355,trace=1,scope=list(lower= ~1,
> upper=~ECO.NAME*ISLAND*DISTANCE.EST*DEPTH500M) ,direction="both")
> fish.vali<-cv.glm(data,stepmodfi.355)
>
>
> Maria Beger
> PhD Candidate
> The Ecology Centre
> School of Integrative Biology
> University of Queensland
> St Lucia, QLD 4072, Australia
> Tel: +61 7 3365 1671
> mbeger at zen.uq.edu.au
> http://www.uq.edu.au/spatialecology/
>
> NRAS - Marshall Islands
> Natural Resource Assessment Surveys Project
> www.nras-conservation.org
>
> Chuuk Lagoon Project
> http://www.earthwatch.org/
>
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>

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595