achisq.boot: Bootstrap Replicates of Pearson's Chi-square Statistic

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

Bootstrap Replicates of Pearson's Chi-square Statistic

Description

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

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

achisq.pboot is used when performing a parametric bootstrap.

Usage

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

Arguments

data	A dataframe containing the data, as specified in DCluster manpage.
i	Permutation generated by the non-parametric 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, boot, achisq, achisq.stat

Examples

library(boot)
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))

niter<-100

#Permutation  model
chq.perboot<-boot(sids, statistic=achisq.boot, R=niter)
plot(chq.perboot)#Display results

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

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

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

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