R: Generate Boostrap Replicates of Stone's Statistic
stone.boot
R Documentation
Generate Boostrap Replicates of Stone's Statistic
Description
Generate bootstrap replicates of Stone's statictic, by means of function
boot from boot package. Notice that these functions should not
be used separately but as argument statistic when calling function
boot.
stone.boot is used when performing a non-parametric bootstrap.
stone.pboot is used when performing a parametric bootstrap.
Usage
stone.boot(data, i, ...)
stone.pboot(...)
Arguments
data
A dataframe with all the data, as explained in the DCluster
manual page.
i
Permutation created in non-parametric bootstrap.
...
Additional arguments passed to the functions.
Value
Both functions return the value of the statistic.
References
Stone, R. A. (1988). Investigating of excess environmental risks around putative sources: Statistical problems and a proposed test. Statistics in Medicine 7,649-660.
See Also
DCluster, boot, stone.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
#All Tests are performed around county 78.
#Permutation model
st.perboot<-boot(sids, statistic=stone.boot, R=niter, region=78)
plot(st.perboot)#Display results
#Multinomial model
st.mboot<-boot(sids, statistic=stone.pboot, sim="parametric",
ran.gen=multinom.sim, R=niter, region=78)
plot(st.mboot)#Display results
#Poisson model
st.pboot<-boot(sids, statistic=stone.pboot, sim="parametric",
ran.gen=poisson.sim, R=niter, region=78)
plot(st.pboot)#Display results
#Poisson-Gamma model
st.pgboot<-boot(sids, statistic=stone.pboot, sim="parametric",
ran.gen=negbin.sim, R=niter, region=78)
plot(st.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
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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/stone.boot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: stone.boot
> ### Title: Generate Boostrap Replicates of Stone's Statistic
> ### Aliases: stone.boot stone.pboot
> ### Keywords: spatial
>
> ### ** 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
>
> #All Tests are performed around county 78.
>
>
> #Permutation model
> st.perboot<-boot(sids, statistic=stone.boot, R=niter, region=78)
> plot(st.perboot)#Display results
>
> #Multinomial model
> st.mboot<-boot(sids, statistic=stone.pboot, sim="parametric",
+ ran.gen=multinom.sim, R=niter, region=78)
> plot(st.mboot)#Display results
>
> #Poisson model
> st.pboot<-boot(sids, statistic=stone.pboot, sim="parametric",
+ ran.gen=poisson.sim, R=niter, region=78)
> plot(st.pboot)#Display results
>
> #Poisson-Gamma model
> st.pgboot<-boot(sids, statistic=stone.pboot, sim="parametric",
+ ran.gen=negbin.sim, R=niter, region=78)
> plot(st.pgboot)#Display results
>
>
>
>
>
>
>
> dev.off()
null device
1
>