gearyc.stat: Compute Geary's C Autocorrelation Statistic

In DCluster: Functions for the Detection of Spatial Clusters of Diseases

Description

Compute Geary's C autocorrelation statistic using either residuals or SMRs by means of cuntion geary from package spdep.

gearyc.stat computes the test statistic and the test using a hi-square distribution whilst gearyc.test performs a bootstrap test.

Usage

gearyc.stat(data, applyto="SMR", ...)
gearyc.test(formula, data, model, R, ...)

Arguments

formula	Formula that specifies the underlying model. The observed cases are the response and the expected number of cases must be specified as an offset in the log scale (see example below). Note that now it is not necessary to use Observed and Expected and that any other names can be used to specify the observed and expected cases.
model	Parametric model to be used in the bootstrap test. One of "param", "multinom", "poisson" or "negbin". See the DCluster manpage for details.
...	Arguments needed by function moran from package spdep. In addition, when calling 'gearyc.test' the remaining arguments in 'gearyc.stat' not included in 'gearyc.test'. This is done so because gearyc.test calls gearyc.stat in order to perform the test.
R	Number of replicates used in the test to compute the significance of the observed value of the test statistic.
data	A dataframe containing the data, as specified in the DCluster manpage.
applyto	A string with the name of the statistic with which calculate Geary's Index. It may be either residulas or SMR.

References

Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician 5, 115-145.

See Also

DCluster, geary, gearyc, gearyc.boot, gearyc.pboot

Examples

library(spdep)
data(nc.sids)
col.W <- nb2listw(ncCR85.nb, zero.policy=TRUE)

sids<-data.frame(Observed=nc.sids$SID74)
sids<-cbind(sids, Expected=nc.sids$BIR74*sum(nc.sids$SID74)/sum(nc.sids$BIR74))

gearyc.stat(data=sids, listw=col.W, n=length(ncCR85.nb), n1=length(ncCR85.nb)-1,
	S0=Szero(col.W) )

gearyc.stat(data=sids, applyto="SMR", listw=col.W, n=length(ncCR85.nb), 
	n1=length(ncCR85.nb)-1,S0=Szero(col.W) )

gearyc.test(Observed~offset(log(Expected)), data=sids, model="poisson", R=99,
   applyto="SMR", listw=col.W, n=length(ncCR85.nb), 
	n1=length(ncCR85.nb)-1,S0=Szero(col.W) )

Example output

Loading required package: boot
Loading required package: spdep
Loading required package: sp
Loading required package: spData
To access larger datasets in this package, install the spDataLarge
package with: `install.packages('spDataLarge',
repos='https://nowosad.github.io/drat/', type='source')`
Loading required package: sf
Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1
Loading required package: MASS
[1] 0.7110422
[1] 0.7110422
Geary's c test of spatial autocorrelation 

	Type of boots.: parametric 
	Model used when sampling: Poisson 
	Number of simulations: 99 
	Statistic:  0.7110422 
	p-value :  0.01 

DCluster documentation built on May 2, 2019, 6:10 p.m.