# geary: Compute Geary's C In r-spatial/spdep: Spatial Dependence: Weighting Schemes, Statistics

## Description

A simple function to compute Geary's C, called by geary.test and geary.mc;

C = \frac{(n-1)}{2∑_{i=1}^{n}∑_{j=1}^{n}w_{ij}} \frac{∑_{i=1}^{n}∑_{j=1}^{n}w_{ij}(x_i-x_j)^2}{∑_{i=1}^{n}(x_i - \bar{x})^2}

geary.intern is an internal function used to vary the similarity criterion.

## Usage

 1 geary(x, listw, n, n1, S0, zero.policy=NULL) 

## Arguments

 x a numeric vector the same length as the neighbours list in listw listw a listw object created for example by nb2listw n number of zones n1 n - 1 S0 global sum of weights zero.policy default NULL, use global option value; if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA

## Value

a list with

 C Geary's C K sample kurtosis of x

## Author(s)

Roger Bivand Roger.Bivand@nhh.no

## References

Cliff, A. D., Ord, J. K. 1981 Spatial processes, Pion, p. 17.

geary.test, geary.mc, sp.mantel.mc
 1 2 3 4 data(oldcol) col.W <- nb2listw(COL.nb, style="W") str(geary(COL.OLD\$CRIME, col.W, length(COL.nb), length(COL.nb)-1, Szero(col.W)))