Generate Bootstrap Replicates of Whittermore's Statistic

Description

Generate bootstrap replicates of Whittermore's statistic 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.

whittermore.boot is used to perform a non-parametric bootstrap

whittermore.pboot is used when using parametric bootstrap.

Usage

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

Arguments

Value

Both functions return the value of the statistic.

References

Whittermore, A. S. and Friend, N. and Byron, W. and Brown, J. R. and Holly, E. A. (1987). A test to detect clusters of disease. Biometrika 74, 631-635.

See Also

DCluster, boot, whittermore, whittermore.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) )
sids<-cbind(sids, x=nc.sids$x, y=nc.sids$y)

#Calculate neighbours based on distance
coords<-as.matrix(sids[,c("x", "y")])

dlist<-dnearneigh(coords, 0, Inf)
dlist<-include.self(dlist)
dlist.d<-nbdists(dlist, coords)

#Calculate weights. They are globally standardised but it doesn't
#change significance.
col.W.whitt<-nb2listw(dlist, glist=dlist.d, style="C")

niter<-100

#Permutation model
wt.boot<-boot(sids, statistic=whittermore.boot, R=niter, listw=col.W.whitt,
	zero.policy=TRUE)
plot(wt.boot)#Display results

#Multinomial model
wt.mboot<-boot(sids, statistic=whittermore.pboot, sim="parametric", 
	ran.gen=multinom.sim,  R=niter,  listw=col.W.whitt, zero.policy=TRUE)
		
plot(wt.mboot)#Display results

#Poisson model
wt.pboot<-boot(sids, statistic=whittermore.pboot, sim="parametric", 
	ran.gen=poisson.sim,  R=niter,  listw=col.W.whitt, zero.policy=TRUE)
		
plot(wt.pboot)#Display results

#Poisson-Gamma model
wt.pgboot<-boot(sids, statistic=whittermore.pboot, sim="parametric", 
	ran.gen=negbin.sim, R=niter, listw=col.W.whitt, zero.policy=TRUE)
plot(wt.pgboot)#Display results

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DCluster)
Loading required package: boot
Loading required package: spdep
Loading required package: sp
Loading required package: Matrix
Loading required package: MASS
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DCluster/whittermore.boot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: whittermore.boot
> ### Title: Generate Bootstrap Replicates of Whittermore's Statistic
> ### Aliases: whittermore.boot whittermore.pboot
> ### Keywords: spatial
> 
> ### ** 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) )
> sids<-cbind(sids, x=nc.sids$x, y=nc.sids$y)
> 
> #Calculate neighbours based on distance
> coords<-as.matrix(sids[,c("x", "y")])
> 
> dlist<-dnearneigh(coords, 0, Inf)
> dlist<-include.self(dlist)
> dlist.d<-nbdists(dlist, coords)
> 
> #Calculate weights. They are globally standardised but it doesn't
> #change significance.
> col.W.whitt<-nb2listw(dlist, glist=dlist.d, style="C")
> 
> niter<-100
> 
> #Permutation model
> wt.boot<-boot(sids, statistic=whittermore.boot, R=niter, listw=col.W.whitt,
+ 	zero.policy=TRUE)
> plot(wt.boot)#Display results
> 
> #Multinomial model
> wt.mboot<-boot(sids, statistic=whittermore.pboot, sim="parametric", 
+ 	ran.gen=multinom.sim,  R=niter,  listw=col.W.whitt, zero.policy=TRUE)
> 		
> plot(wt.mboot)#Display results
> 
> #Poisson model
> wt.pboot<-boot(sids, statistic=whittermore.pboot, sim="parametric", 
+ 	ran.gen=poisson.sim,  R=niter,  listw=col.W.whitt, zero.policy=TRUE)
> 		
> plot(wt.pboot)#Display results
> 
> #Poisson-Gamma model
> wt.pgboot<-boot(sids, statistic=whittermore.pboot, sim="parametric", 
+ 	ran.gen=negbin.sim, R=niter, listw=col.W.whitt, zero.policy=TRUE)
> plot(wt.pgboot)#Display results
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>