Implements a spatial extension of the random forest algorithm (Georganos et al. (2019) <doi:10.1080/10106049.2019.1595177>). Future updates include more local machine learning methods as well as a geographically weighted random forest.
Changelog
Version: 0.1.3 (9 May 2019)
grf: This function refers to a geographical (local) version of the popular Random Forest algorithm
predict.grf: Predict Method for Geographical Random Forest
random.test.data: Random data generator
Datasets
Income: Mean household income at local authorities in Greece in 2011
Download SpatialML
SpatialML is available at the Comprehensive R Archive Network (CRAN): https://CRAN.R-project.org/package=SpatialML. A reference manual for SpatialML is available here…
References
(2019) Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling, Geocarto International, DOI: 10.1080/10106049.2019.1595177