geary: Compute Geary's C

In spdep: Spatial Dependence: Weighting Schemes, Statistics

Compute Geary's C

Description

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

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

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

Usage

geary(x, listw, n, n1, S0, zero.policy=attr(listw, "zero.policy"), scale=TRUE)

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 attr(listw, "zero.policy") as set when listw was created, if attribute not set, use global option value; if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
scale	default TRUE, may be FALSE to revert changes made to accommodate localC in November 2021 (see #151)

Value

a list with

C	Geary's C
K	sample kurtosis of x

Author(s)

Roger Bivand [e-mail]

References

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

See Also

geary.test, geary.mc, sp.mantel.mc

Examples

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)))

spdep documentation built on Sept. 13, 2024, 5:07 p.m.