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 (<btup...@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 <mspinol...@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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