Display a sort of box plot
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 boxwidth as the number of observations and let the function work it out.
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,...)
x,y |
Vectors of numeric values representing measures of central tendency. |
uinner,linner |
Vectors of numeric values representing "inner" measures of dispersion. |
ulim,llim |
Vectors of numeric values representing "outer" measures of dispersion. |
boxwidth |
Optional widths for the boxes. |
intervals |
Whether the values for dispersion are intervals (TRUE) or absolute limits (FALSE). |
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. |
pch |
The symbol to be used to represent the measure(s) of central tendency in the box. |
main |
The title for the plot (i.e. main). |
xlab,ylab |
The x and y axis labels. |
xaxlab |
Optional labels for the boxes. |
col |
The fill colors for the "inner" rectangles. |
do.first |
An expression that will be evaluated before anything is displayed. |
... |
additional arguments passed to the dispersion function. |
nil
Jim Lemon - thanks to Gianni Lavaredo for the suggestion
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")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.