autocor: Global Spatial Autocorrelation Statistics

Description Usage Arguments Details Value Author(s) References Examples

Description

Functions to calculate Moran's I and Geary's c statistics.

Usage

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moran(x,d1,d2,...) 
geary(x,d1,d2,...) 

Arguments

x

a raster object (RasterLayer or SpatialPointsDataFrame or SpatialPolygonsDataFrame

d1

lower bound local distance, or an object of class neighbours created by dneigh when x is SpatialPoints or SpatialPolygons

d2

upper bound local distance

...

additional arguments including zcol (when x is Spatial* object, specifies the name of the variable in the dataset; longlat (when x is Spatial* object, spacifies whether the dataset has a geographic coordinate system

Details

moran and geary are two functions to measure global spatial autocorrelation within the range of distance specified through d1 and d2. It returns a single numeric value than can show the degree of spatial autocorrelation in the whole dataset.

Value

A numeric value.

Author(s)

Babak Naimi naimi.b@gmail.com

http://r-gis.net

References

Naimi, B., Hamm, N. A., Groen, T. A., Skidmore, A. K., Toxopeus, A. G., & Alibakhshi, S. (2019). ELSA: Entropy-based local indicator of spatial association. Spatial statistics, 29, 66-88.

Examples

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file <- system.file('external/dem_example.grd',package='elsa')
r <- raster(file)

moran(r, d1=0, d2=2000)

geary(r, d1=0, d2=2000)

babaknaimi/elsa documentation built on March 20, 2020, 5:22 p.m.