plants_xy

Spatial coordinates (longitude and latitude) extracted from plants_df for use in spatial modeling functions.

datasets

Automatic generation and selection of spatial predictors for Random Forest models fitted to spatially structured data. Spatial predictors are constructed from a distance matrix among training samples using Moran's Eigenvector Maps (MEMs; Dray, Legendre, and Peres-Neto 2006 <DOI:10.1016/j.ecolmodel.2006.02.015>) or the RFsp approach (Hengl et al. <DOI:10.7717/peerj.5518>). These predictors are used alongside user-supplied explanatory variables in Random Forest models. The package provides functions for model fitting, multicollinearity reduction, interaction identification, hyperparameter tuning, evaluation via spatial cross-validation, and result visualization using partial dependence and interaction plots. Model fitting relies on the 'ranger' package (Wright and Ziegler 2017 <DOI:10.18637/jss.v077.i01>).

Blas M. Benito

spatialRF

Easy Spatial Modeling with Random Forest

plants_xy function

A data frame with 227 rows and 2 columns:<ul>
<li><code>x</code>: Longitude in degrees (WGS84).</li>
<li><code>y</code>: Latitude in degrees (WGS84).</li>
</ul>

plants_xy: Coordinates for plant richness data

Description

Usage

Arguments

Format

See Also