[R-sig-eco] Categorical variables Maxent dismo

[Irene Rojo]

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 using gmail.com>) escribió:

> 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 using 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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>>
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