mem: Moran's Eigenvector Maps of a distance matrix

In spatialRF: Easy Spatial Modeling with Random Forest

Moran's Eigenvector Maps of a distance matrix

Description

Computes the positive Moran's Eigenvector Maps of a distance matrix.

Usage

mem(
  distance.matrix = NULL,
  distance.threshold = 0,
  colnames.prefix = "mem"
)

Arguments

distance.matrix	Distance matrix. Default: NULL.
distance.threshold	Numeric vector with distance thresholds defining different neighborhood extents within the distance matrix, Default: 0
colnames.prefix	Character, name prefix for the output columns. Default: "mem"

Details

Takes the distance matrix x, double-centers it with double_center_distance_matrix(), applies eigen, and returns eigenvectors with positive normalized eigenvalues (a.k.a Moran's Eigenvector Maps, or MEMs). These MEMs are later used as spatial predictors by rf_spatial().

Value

A data frame with positive Moran's Eigenvector Maps.

See Also

mem_multithreshold(), rf_spatial()

Examples

if(interactive()){

 #loading example distance matrix
 data(distance_matrix)

 #Moran's Eigenvector Maps of the distance matrix
 mem <- mem(x = distance_matrix)

}

spatialRF documentation built on Aug. 19, 2022, 5:23 p.m.