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 -- *Manuel Sp?nola, Ph.D.* Instituto Internacional en Conservaci?n y Manejo de Vida Silvestre Universidad Nacional Apartado 1350-3000 Heredia COSTA RICA mspinola at una.cr <mspinola at una.ac.cr> mspinola10 at gmail.com Tel?fono: (506) 8706 - 4662 Sitio web institucional: ICOMVIS <http://www.icomvis.una.ac.cr/index.php/manuel> Sitio web personal: Sitio personal <https://mspinola-sitioweb.netlify.app
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