# R/outbox.R In WRS2: A Collection of Robust Statistical Methods

```outbox<-function(x,mbox=FALSE,gval=NA,plotit=FALSE,STAND=FALSE){
#
# This function detects outliers using the
# boxplot rule, but unlike the R function boxplot,
# the ideal fourths are used to estimate the quartiles.
#
# Setting mbox=T results in using the modification
# of the boxplot rule suggested by Carling (2000).
#
x<-x[!is.na(x)] # Remove missing values
if(plotit)boxplot(x)
n<-length(x)
temp<-idealf(x)
if(mbox){
if(is.na(gval))gval<-(17.63*n-23.64)/(7.74*n-3.71)
cl<-median(x)-gval*(temp\$qu-temp\$ql)
cu<-median(x)+gval*(temp\$qu-temp\$ql)
}
if(!mbox){
if(is.na(gval))gval<-1.5
cl<-temp\$ql-gval*(temp\$qu-temp\$ql)
cu<-temp\$qu+gval*(temp\$qu-temp\$ql)
}
flag<-NA
outid<-NA
vec<-c(1:n)
for(i in 1:n){
flag[i]<-(x[i]< cl || x[i]> cu)
}
if(sum(flag)==0)outid<-NULL
if(sum(flag)>0)outid<-vec[flag]
keep<-vec[!flag]
outval<-x[flag]
n.out=sum(length(outid))
list(out.val=outval,out.id=outid,keep=keep,n=n,n.out=n.out,cl=cl,cu=cu)
}
```

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WRS2 documentation built on May 2, 2019, 4:46 p.m.