pottwhitt.boot {DCluster} | R Documentation |
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