Random forest classification combined with spatial linear model prediction

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 Sp?nola 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 at bigelow.org>)
escribi?:

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 Sp?nola <mspinola10 at 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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