View source: R/moran_multithreshold.R
moran_multithreshold | R Documentation |
Applies moran()
to different distance thresholds at the same time.
moran_multithreshold( x = NULL, distance.matrix = NULL, distance.thresholds = NULL, verbose = TRUE )
x |
Numeric vector, generally model residuals, Default: |
distance.matrix |
Distance matrix among cases in |
distance.thresholds |
Numeric vector, distances below each value are set to 0 on separated copies of the distance matrix for the computation of Moran's I at different neighborhood distances. If |
verbose |
Logical, if |
Using different distance thresholds helps to take into account the uncertainty about what "neighborhood" means in ecological systems (1000km in geological time means little, but 100m might be quite a long distance for a tree to disperse seeds over), and allows to explore spatial autocorrelation of model residuals for several minimum-distance criteria at once.
A named list with the slots:
df
: Data frame with the results of moran per distance threshold.
plot
: A plot of Moran's I across distance thresholds.
max.moran
: Maximum value of Moran's I across thresholds.
max.moran.distance.threshold
: Distance threshold with the maximum Moran's I value.
moran()
if(interactive()){ #loading example data data(distance_matrix) data(plant_richness) #computing Moran's I for the response variable at several reference distances out <- moran_multithreshold( x = plant_richness$richness_species_vascular, distance.matrix = distance_matrix, distance.thresholds = c(0, 100, 1000, 10000), plot = TRUE ) out }
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