globalG.test {spdep}R Documentation

test for spatial autocorrelation

Description

.

Usage

globalG.test(x, listw, zero.policy=FALSE, alternative="greater", spChk=NULL)

Arguments

x a numeric vector the same length as the neighbours list in listw
listw a listw object created for example by nb2listw
zero.policy if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA
alternative a character string specifying the alternative hypothesis, must be one of "greater" (default), "less" or "two.sided".
spChk should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use get.spChkOption()

Value

A list with class htest containing the following components:

statistic the value of the standard deviate of Moran's I.
p.value the p-value of the test.
estimate the value of the observed statistic, its expectation and variance.
alternative a character string describing the alternative hypothesis.
data.name a character string giving the name(s) of the data.

Author(s)

Hisaji ONO hi-ono@mn.xdsl.ne.jp and Roger Bivand Roger.Bivand@nhh.no

References

Getis. A, Ord, J. K. 1992 The analysis of spatial association by use of distance statistics, Geographical Analysis, 24, p. 195.

See Also

localG

Examples

data(nc.sids)
sidsrate79 <- (1000*nc.sids$SID79)/nc.sids$BIR79
names(sidsrate79) <- rownames(nc.sids)
dists <- c(10, 20, 30, 33, 40, 50, 60, 70, 80, 90, 100)
ndists <- length(dists)
ZG <- numeric(length=ndists)
milesxy <- cbind(nc.sids$east, nc.sids$north)
for (i in 1:ndists) {
  thisnb <- dnearneigh(milesxy, 0, dists[i], row.names=rownames(nc.sids))
  thislw <- nb2listw(thisnb, style="B", zero.policy=TRUE)
  ZG[i] <- globalG.test(sidsrate79, thislw, zero.policy=TRUE)$statistic
}
cbind(dists, ZG)

[Package spdep version 0.3-12 Index]