Hola Diego,
Thank you very much for your reply. I have tried the dropLayer function as
you suggest but it removes the variable ("Fence" in your example) from the
raster stack "predictors" with all the variables, so I think it is not
doing what I wanted. Thanks a lot anyway for your time.
Any other advice would be much appreciated.
Regards,
Irene
El vie, 15 ene 2021 a las 10:10, Diego GT (<dgt3087 at gmail.com>) escribi?:
Hola Irene
I have been learning Maxent this week. In my case I have one categorical
variable. I tried the ENMeval package there is an option to name
categoricals="your variable". On the dismo package I think you have to
pred_nf <- dropLayer(predictors, 'Fence') to do the training and
background and then in the model you attached them again.
xm <- maxent(predictors, pres_train, factors='Fence')
I don't know how it works statistically. But I hope it helps.
Cheers
Diego
On Fri, 15 Jan 2021 at 19:33, Irene Rojo <ire.rojo at gmail.com> wrote:
Dear all,
I am running Maxent models with dismo package. I have several categorical
variables, which have been specified in the model as factors, but the
output gives me only the contribution of the whole variable and not the
category. Is there a way that the analysis reports the category of the
variable which contributes the most? I have not been able to find how to
do
it.
Thanks a lot,
Irene
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