DCluster (version 0.2-7)

moranI.boot: Generate Bootstrap Replicates of Moran's I Autocorrelation Statistic

Description

Generate bootstrap replicates of Moran's I autocorrelation statistic, by means of function boot form boot library. Notice that these functions should not be used separately but as argument statistic when calling function boot.

moranI.boot is used when performing a non-parametric bootstrap.

moranI.pboot is used when performing a parametric bootstrap.

Usage

moranI.boot(data, i, ...)
moranI.pboot(...)

Arguments

data

A dataframe containing the data, as specified in the DClustermanpage.

i

Permutation generated by the bootstrap procedure

...

Aditional arguments passed when performing a bootstrap.

Value

Both functions return the value of the statistic.

References

Moran, P. A. P. (1948). The interpretation os statistical maps. Journal of the Royal Statistical Society, Series B 10, 243-251.

See Also

DCluster, boot, moranI, moranI.stat

Examples

# NOT RUN {
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)) 

niter<-100

#Permutation model
moran.boot<-boot(sids, statistic=moranI.boot, R=niter, listw=col.W, 
	n=length(ncCR85.nb), S0=Szero(col.W) )
plot(moran.boot)#Display results

#Multinomial model
moran.mboot<-boot(sids, statistic=moranI.pboot, sim="parametric", 
	ran.gen=multinom.sim,  R=niter, listw=col.W,n=length(ncCR85.nb), 
	S0=Szero(col.W) )
plot(moran.mboot)#Display results

#Poisson model
moran.pboot<-boot(sids, statistic=moranI.pboot, sim="parametric", 
	ran.gen=poisson.sim,  R=niter, listw=col.W,n=length(ncCR85.nb),
	S0=Szero(col.W) )
		
plot(moran.pboot)#Display results

#Poisson-Gamma model
moran.pgboot<-boot(sids, statistic=moranI.pboot, sim="parametric", 
	ran.gen=negbin.sim, R=niter,  listw=col.W,n=length(ncCR85.nb),
	S0=Szero(col.W) )
		
plot(moran.pgboot)#Display results
# }