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SpatialML  

Spatial Machine Learning
View on CRAN: Click here


Download and install SpatialML package within the R console
Install from CRAN:
install.packages("SpatialML")

Install from Github:
library("remotes")
install_github("cran/SpatialML")

Install by package version:
library("remotes")
install_version("SpatialML", "0.1.7")



Attach the package and use:
library("SpatialML")
Maintained by
Stamatis Kalogirou
[Scholar Profile | Author Map]
First Published: 2019-05-09
Latest Update: 2023-11-08
Description:
Implements a spatial extension of the random forest algorithm (Georganos et al. (2019) <doi:10.1080/10106049.2019.1595177>). Allows for a geographically weighted random forest regression including a function to find the optical bandwidth. (Georganos and Kalogirou (2022) <https://www.mdpi.com/2220-9964/11/9/471>).
How to cite:
Stamatis Kalogirou (2019). SpatialML: Spatial Machine Learning. R package version 0.1.7, https://cran.r-project.org/web/packages/SpatialML. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.1.3 (2019-05-09 17:10), 0.1.4 (2022-06-20 22:30), 0.1.5 (2022-09-02 09:20), 0.1.6 (2023-11-08 01:20)
Other packages that cited SpatialML R package
View SpatialML citation profile
Other R packages that SpatialML depends, imports, suggests or enhances
Complete documentation for SpatialML
Functions, R codes and Examples using the SpatialML R package
Some associated functions: Income . grf.bw . grf . predict.grf . random.test.data . rf.mtry.optim . 
Some associated R codes: grf.R . grf.bw.R . predict.grf.R . random.test.data.R . rf.mtry.optim.R .  Full SpatialML package functions and examples
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