Learn R Programming

pgirmess (version 1.3.9)

correlog: Computes Moran's or Geary's coefficients on distance classes

Description

Computes Moran's or Geary's coefficients on distance classes from a set of spatial coordinates and corresponding z values

Usage

correlog(coords, z, method="Moran", nbclass = NULL,...)

Arguments

coords
a two columns array, data.frame or matrix of spatial coordinates. Column 1 = X, Column 2 = Y.
z
a vector for the values at each location. Must have the same length as the row number of coords
method
the method used. Must be "Moran" (default) or "Geary"
nbclass
number of bins. If NULL Sturges method is used to compute an optimal number
...
further arguments to pass to e.g. moran.test or geary.test

Value

  • An object of class "correlog", a matrix including:
  • classbin centers
  • Ithe coefficient values
  • p.valueprobability of Ho
  • nthe number of pairs

Warning

Computing can take a long time for large data sets

Details

Uses the library spdep including moran.test or geary.test. These methods assume the data are normally distributed. Distances are euclidian and in the same unit as the spatial coordinates. Moran's Ho: I values larger than 0 due to chance; Geary's Ho: C values lesser than 1 due to chance. Correlog has print and plot methods; statistically significant values (p

References

see library spdep

See Also

geary.test, moran.test

Examples

Run this code
library(spdep)
data(oldcol)
attach(COL.OLD)
coords<-cbind(X,Y)
res<-correlog(coords,CRIME)
plot(res)

res<-correlog(coords,CRIME,method="Geary")
plot(res)

Run the code above in your browser using DataLab