globalG.test: Global G test for spatial autocorrelation

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/globalG.R

Description

The global G statistic for spatial autocorrelation, complementing the local Gi LISA measures: localG.

Usage

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globalG.test(x, listw, zero.policy=NULL, alternative="greater",
 spChk=NULL, adjust.n=TRUE, B1correct=TRUE)

Arguments

x

a numeric vector the same length as the neighbours list in listw

listw

a listw object created for example by nb2listw; if a sequence of distance bands is to be used, it is recommended that the weights style be binary (one of c("B", "C", "U")).

zero.policy

default NULL, use global option value; 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()

adjust.n

default TRUE, if FALSE the number of observations is not adjusted for no-neighbour observations, if TRUE, the number of observations is adjusted

B1correct

default TRUE, if TRUE, the erratum referenced below: "On page 195, the coefficient of W2 in B1, (just below center of the page) should be 6, not 3." is applied; if FALSE, 3 is used (as in CrimeStat IV)

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 [email protected] and Roger Bivand [email protected]

References

Getis. A, Ord, J. K. 1992 The analysis of spatial association by use of distance statistics, Geographical Analysis, 24, p. 195; see also Getis. A, Ord, J. K. 1993 Erratum, Geographical Analysis, 25, p. 276.

See Also

localG

Examples

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example(nc.sids)
sidsrate79 <- (1000*nc.sids$SID79)/nc.sids$BIR79
dists <- c(10, 20, 30, 33, 40, 50, 60, 70, 80, 90, 100)
ndists <- length(dists)
ZG <- vector(mode="list", length=ndists)
names(ZG) <- as.character(dists)
milesxy <- cbind(nc.sids$east, nc.sids$north)
for (i in 1:ndists) {
  thisnb <- dnearneigh(milesxy, 0, dists[i])
  thislw <- nb2listw(thisnb, style="B", zero.policy=TRUE)
  ZG[[i]] <- globalG.test(sidsrate79, thislw, zero.policy=TRUE)
}
t(sapply(ZG, function(x) c(x$estimate[1], x$statistic, p.value=unname(x$p.value))))
for (i in 1:ndists) {
  thisnb <- dnearneigh(milesxy, 0, dists[i])
  thislw <- nb2listw(thisnb, style="B", zero.policy=TRUE)
  ZG[[i]] <- globalG.test(sidsrate79, thislw, zero.policy=TRUE, alternative="two.sided")
}
t(sapply(ZG, function(x) c(x$estimate[1], x$statistic, p.value=unname(x$p.value))))

Example output

Loading required package: sp
Loading required package: Matrix

nc.sds> require(maptools)
Loading required package: maptools
Checking rgeos availability: TRUE

nc.sds> nc.sids <- readShapePoly(system.file("etc/shapes/sids.shp", package="spdep")[1],
nc.sds+   ID="FIPSNO", proj4string=CRS("+proj=longlat +ellps=clrk66"))
NOTE: rgdal::checkCRSArgs: no proj_defs.dat in PROJ.4 shared files

nc.sds> rn <- sapply(slot(nc.sids, "polygons"), function(x) slot(x, "ID"))

nc.sds> ncCC89_nb <- read.gal(system.file("etc/weights/ncCC89.gal", package="spdep")[1],
nc.sds+   region.id=rn)

nc.sds> ncCR85_nb <- read.gal(system.file("etc/weights/ncCR85.gal", package="spdep")[1],
nc.sds+   region.id=rn)

nc.sds> ## Not run: 
nc.sds> ##D plot(nc.sids, border="grey")
nc.sds> ##D plot(ncCR85_nb, coordinates(nc.sids), add=TRUE, col="blue")
nc.sds> ##D plot(nc.sids, border="grey")
nc.sds> ##D plot(ncCC89_nb, coordinates(nc.sids), add=TRUE, col="blue")
nc.sds> ## End(Not run)
nc.sds> 
nc.sds> 
nc.sds> 
Warning message:
use rgdal::readOGR or sf::st_read 
    Global G statistic standard deviate   p.value
10         0.000612124       0.81651489 0.2071029
20         0.014698945       0.27046614 0.3934008
30         0.039947466      -0.11849772 0.5471634
33         0.053122713       0.40157023 0.3440002
40         0.074002794      -0.04345713 0.5173314
50         0.114717434       0.58686472 0.2786473
60         0.154575526      -0.35823892 0.6399177
70         0.198390232      -0.27864299 0.6097406
80         0.246069725      -0.18791364 0.5745278
90         0.300734634       0.11457610 0.4543906
100        0.348799963       0.31591356 0.3760341
    Global G statistic standard deviate   p.value
10         0.000612124       0.81651489 0.4142057
20         0.014698945       0.27046614 0.7868017
30         0.039947466      -0.11849772 0.9056733
33         0.053122713       0.40157023 0.6880003
40         0.074002794      -0.04345713 0.9653371
50         0.114717434       0.58686472 0.5572946
60         0.154575526      -0.35823892 0.7201645
70         0.198390232      -0.27864299 0.7805188
80         0.246069725      -0.18791364 0.8509443
90         0.300734634       0.11457610 0.9087811
100        0.348799963       0.31591356 0.7520681

spdep documentation built on Sept. 2, 2017, 1:11 a.m.