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\name{box.heresy}
\alias{box.heresy}
\title{Display a sort of box plot}
\usage{
box.heresy(x,y,uinner,linner,ulim,llim,boxwidth=NULL,
intervals=FALSE,arrow.cap=NULL,pch=22,main="",xlab="",ylab="",
xaxlab=NULL,col="white",do.first=NULL,...)
}
\arguments{
\item{x,y}{Vectors of numeric values representing measures of central tendency.}
\item{uinner,linner}{Vectors of numeric values representing "inner" measures of
dispersion.}
\item{ulim,llim}{Vectors of numeric values representing "outer" measures of
dispersion.}
\item{boxwidth}{Optional widths for the boxes.}
\item{intervals}{Whether the values for dispersion are intervals (TRUE) or
absolute limits (FALSE).}
\item{arrow.cap}{The width of the cap on the "whiskers" relative to the width
of the plot. Defaults to the same width as the outer box.}
\item{pch}{The symbol to be used to represent the measure(s) of central tendency
in the box.}
\item{main}{The title for the plot (i.e. \samp{main}).}
\item{xlab,ylab}{The x and y axis labels.}
\item{xaxlab}{Optional labels for the boxes.}
\item{col}{The fill colors for the "inner" rectangles.}
\item{do.first}{An expression that will be evaluated before anything is displayed.}
\item{...}{additional arguments passed to the \samp{dispersion} function.}
}
\description{
\samp{box.heresy} displays a box plot in which a symbol represents a measure of
central tendency, a surrounding box that represents an "inner" measure of dispersion
(e.g. standard error) and whiskers represent an "outer" measure of dispersion
(e.g. standard deviation). The function is pretty basic at this time and will
probably change a bit.
The argument "intervals" is particularly important, and can wreak
havoc on the resulting plot. The default of FALSE means that the
values passed to the inner and outer measures of dispersion are
absolute, not intervals away from the measure of central tendency.
Mixing absolute and relative values will always lead to errors and
typically a very strange looking plot. It is probably easiest to
calculate the absolute values before calling box.heresy. The first and
second examples show how intervals=FALSE and intervals=TRUE can be used.
One of the first changes is to allow varying box widths. The user can specify
the box widths as a vector of numeric values at least as long as the number
of boxes to be displayed. The usual reason for doing this is to display widths
that are proportional to the number of observations. A useful start is to pass
\samp{boxwidth} as the number of observations and let the function work it out.
}
\value{nil}
\author{Jim Lemon - thanks to Gianni Lavaredo for the suggestion}
\keyword{misc}
\seealso{\link{plot}, \link{boxplot}}
\examples{
y1<-runif(20,2,10)
y2<-rnorm(30,6,2)
y3<-sample(0:20,40,TRUE)
Ns<-c(20,30,40)
ymean<-c(mean(y1),mean(y2),mean(y3))
y1inner<-quantile(y1,probs=c(.16,.84))
y2inner<-c(ymean[2]+sd(y2),ymean[2]-sd(y2))
y3inner<-quantile(y3,probs=c(.16,.84))
uinner<-c(y1inner[1],y2inner[1],y3inner[1])
linner<-c(y1inner[2],y2inner[2],y3inner[2])
ulim<-c(max(y1),max(y2),max(y3))
llim<-c(min(y1),min(y2),min(y3))
box.heresy(ymean,uinner=uinner,linner=linner,ulim=ulim,llim=llim,boxwidth=Ns,
main="Boxplot of means, central spread and range",xlab="Distribution",
xaxlab=c("Uniform","Normal","Sample"))
y1outer<-
y<-runif(5)
ulim<-runif(5)
llim<-runif(5)
uinner<-ulim/2
linner<-llim/2
box.heresy(y,uinner=uinner,linner=linner,ulim=ulim,llim=llim,
intervals=TRUE,main="The heretical boxplot",
xlab="Number of observations",ylab="Value")
}
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