pottwhitt.boot: Bootstrap Replicates of Potthoff-Whittinghill's Statistic

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

Bootstrap Replicates of Potthoff-Whittinghill's Statistic

Description

Generate bootstrap replicates of Potthoff-Whittinghill's statistic (function pottwhitt.stat), by means of function boot from the boot library. Notice that these functions should not be used separately but as argument statistic when calling function boot.

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

pottwhitt.pboot is used when performing a parametric bootstrap.

Usage

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

Arguments

data	A dataframe containing the data, as specified in the DCluster manual page.
i	Permutation generated by the bootstrap procedure
...	Additional arguments passed when performing a bootstrap.

Value

Both functions return the value of the statistic.

References

Potthoff, R. F. and Whittinghill, M.(1966). Testing for Homogeneity: I. The Binomial and Multinomial Distributions. Biometrika 53, 167-182.

Potthoff, R. F. and Whittinghill, M.(1966). Testing for Homogeneity: The Poisson Distribution. Biometrika 53, 183-190.

See Also

DCluster, pottwhitt, pottwhitt.stat

Examples

library(spdep)

data(nc.sids)

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

niter<-100


#Permutation model
pw.boot<-boot(sids, statistic=pottwhitt.boot, R=niter)
plot(pw.boot)#Plot results


#Multinomial model
pw.mboot<-boot(sids, statistic=pottwhitt.pboot, sim="parametric", ran.gen=multinom.sim,  R=niter)
plot(pw.mboot)#Plot results

#Poisson model
pw.pboot<-boot(sids, statistic=pottwhitt.pboot, sim="parametric", ran.gen=poisson.sim,  R=niter)
plot(pw.pboot)#Plot results

#Poisson-Gamma model
pw.pgboot<-boot(sids, statistic=pottwhitt.pboot, sim="parametric", ran.gen=negbin.sim, R=niter)
plot(pw.pgboot)#Plot results

DCluster documentation built on May 29, 2024, 3:41 a.m.