achisq.boot {DCluster} | R Documentation |
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.
achisq.boot(data, i, ...) achisq.pboot(...)
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. |
Both functions return the value of the statistic.
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.
DCluster, boot, achisq, achisq.stat
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