[Biomod-commits] (no subject)

[Damien Georges]

Dear Javier,

Your scripts seem to be ok.
Do you get a console error message when you make ensemble and/or 
projections?

Is 'myExpl' a rater or a dataframe? If it is a raster you can access 
projected raster with get_prediction() function else you will get a 
data.frame that you will have to rasterize manually.

Hope that helps,
Damien.

PS : If you don't work with the last version of the package, I recommend 
you to update it (**|install.packages("biomod2", 
repos="http://R-Forge.R-project.org")|**) That will probably solve your 
evaluation issue.


On 23/08/2013 19:23, Javier Nori wrote:
> Dear all!
>
> I am new with Biomod. I'm trying to perform an ensemble between results of
> five algorithms ('MARS','GAM','GBM', 'MAXENT', 'GLM', 'FDA'), using
> Pres-PAbs data. I have not problems to generate and project the results of
> the individual models. However probably i'am making a mistake in the
> emsemble of them or in the projection' script because I cannot generate the
> rasters of the ensemble. In addition, I cannot obtain the values of the
> evaluation index of the ensemble (*Error: Error in (function (classes,
> fdef, mtable)  :   unable to find an inherited method for function
> ‘getModelsEvaluations’ for signature ‘"BIOMOD.EnsembleModeling.out"’*)
>
> Could anyone help me please?
>
> Thanks in advance!!
>
> below I attached the scripts for projection and ensemble
> **
> Ensemble
> myBiomodEM <- BIOMOD_EnsembleModeling(
> modeling.output = myBiomodModelOut,
> chosen.models = 'all',
> em.by='all',
> eval.metric = c('ROC'),
> eval.metric.quality.threshold = c(0.8),
> prob.mean = T,
> prob.cv = T,
> prob.ci = T,
> prob.ci.alpha = 0.05,
> prob.median = T,
> committee.averaging = T,
> prob.mean.weight = T,
> prob.mean.weight.decay = 'proportional' )
>
> Projection
> myBiomodProj <- BIOMOD_Projection(
> modeling.output = myBiomodModelOut,
> new.env = myExpl,
> proj.name = 'current',
> selected.models = 'all',
> binary.meth = 'TSS',
> filtered.meth ='TSS',
> cmpress = 'gzip',
> clamping.mask = T,
> output.format = '.img')
>