kullnagar.boot: Generate Bootstrap Replicates of Kulldorff and Nagarwalla's Statistic

Description

Generate bootstrap replicates of Kulldorff and Nagarwalla's statistic, by calling functions boot and kullnagar.stat.

kullnagar.boot is used when using non-parametric bootstrap to estimate the distribution of the statistic.

kullnagar.pboot is used when performing parametric bootstrap.

Usage

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

Arguments

data

A dataframe with the data as explained in DCluster.

Permutation created in non-parametric bootstrap.

...

Additional arguments passed to the functions.

Value

Both functions return the value of the statistic.

References

Kulldorff, Martin and Nagarwalla, Neville (1995). Spatial Disease Clusters: Detection and Inference. Statistics in Medicine 14, 799-810.

Examples

Run this code

# NOT RUN {
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))
sids<-cbind(sids, Population=nc.sids$BIR74, x=nc.sids$x, y=nc.sids$y)

niter<-100

#Permutation  model
kn.perboot<-boot(sids, statistic=kullnagar.boot, R=niter, fractpop=.2)
plot(kn.perboot)#Display results

#Multinomial model
kn.mboot<-boot(sids, statistic=kullnagar.pboot, sim="parametric", 
	ran.gen=multinom.sim,  R=niter, fractpop=.2)
plot(kn.mboot)#Display results

#Poisson model
kn.pboot<-boot(sids, statistic=kullnagar.pboot, sim="parametric", 
	ran.gen=poisson.sim,  R=niter, fractpop=.2)
plot(kn.pboot)#Display results

#Poisson-Gamma model
kn.pgboot<-boot(sids, statistic=kullnagar.pboot, sim="parametric", 
	ran.gen=negbin.sim, R=niter, fractpop=.2)
plot(kn.pgboot)#Display results


# }