[R-sig-Geo] Random forest classification combined with spatial linear model prediction

[Edzer Pebesma]

I'm not entirely sure what you mean by spatial linear model, but it may 
be worth looking into 
https://cran.r-project.org/web/packages/RandomForestsGLS/index.html

The paper referenced in there, 
https://doi.org/10.1080/01621459.2021.1950003 , is worth reading!

On 20/02/2025 22:50, Manuel Spínola wrote:
> Thank you Ben,
> 
> I know tidysdm, and it’s a great package, but I don’t think it accounts for
> spatial structure in the way I expect—though I could be wrong. It does use
> spatial_block_cv, which likely considers the spatial component.
> 
> It is my understanding that sprflm from the spmodel package applies kriging
> to the residuals.
> 
> 
> Manuel
> 
> 
> 
> 
> El jue, 20 feb 2025 a las 15:20, Ben Tupper (<btupper using bigelow.org>)
> escribió:
> 
>> Hi,
>>
>> I'm not sure I fully understand what you are asking for, but are
>> describing something like tidysdm
>> <https://evolecolgroup.github.io/tidysdm/>?
>>
>> Cheers,
>> Ben
>>
>> On Thu, Feb 20, 2025 at 3:16 PM Manuel Spínola <mspinola10 using gmail.com>
>> wrote:
>>
>>> Dear list members,
>>>
>>> Is there any R package that combines random forest classification and
>>> spatial linear model prediction?
>>>
>>> The spmodel can fit this type of model but only for random forest
>>> regression according to the help document.
>>>
>>> My goal is to work with species distribution modelling with random forest
>>> but includes the spatial structure of the data.
>>>
>>> Manuel
>>>
>>>
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>>>>
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>>
> 

-- 
Edzer Pebesma (he/him)
Universität Münster, Institute for Geoinformatics
Heisenbergstrasse 2, 48149 Münster, Germany
Phone: +49 251 8333081