caroline (version 0.5.0)

volins: Plot a Series of Vioplot Violins

Description

This is an improvment on the original vioplot function (combination of a box plot and a kernel density plot). You can now pass a list of violins and a list of colors. Optionally it also returns statistics on the distributions as well.

Usage

violins(x, by, range = 1.5, h = NULL, ylim = NULL, names =
                 NULL, horizontal = FALSE, col = "transparent", border
                 = "black", lty = 1, lwd = 1, rectCol = "grey50",
                 colMed = "grey80", pchMed = 19, at, add = FALSE, wex =
                 1, drawRect = TRUE, main = "", connect = TRUE, 
                 connect.col='lightgreen', connect.lty=1, connect.lwd=1,
                 xlab='', ylab='', stats=FALSE, ci.median_mu = TRUE)

Arguments

x

list of vectors or a dataframe

by

accepts 'by' object for grouping

range

a factor to calculate the upper/lower adjacent values.

h

the height for the density estimator, if omit as explained in sm.density, h will be set to an optimum.

ylim

y limits.

names

one label, or a vector of labels for the datas must match the number of datas given.

horizontal

description of var 1.

col,border,lty,lwd

Graphical parameters for the violin passed to lines and polygon.

rectCol,colMed,pchMed

Graphical parameters to control the look of the box.

at

position of each violin. Default to 1:n

add

logical. if FALSE (default) a new plot is created

wex

relative expansion of the violin.

drawRect

logical. the box is drawn if TRUE.

main

main title for the plot.

connect

connects a violin plot series at the medians with line segments

connect.col

line color of the median connecting line segments

connect.lty

line type of the median connecting line segments

connect.lwd

line width of the median connecting line segments

xlab

x axis label

ylab

y axis label

stats

print out statistics

ci.median_mu

boolean for 95 pct ci.median and huber.mu M-estimator calculations

Value

• a series of violin plots

See Also

vioplot

Examples

n <- rnorm(130, 10, 3)
p <- rpois(110, 4)
u <- runif(300, 0, 20)
l <- rlnorm(130, log(2))
g <- rgamma(140, 3)
e <- rexp(160)

violins(list(e=e, p=p,u=u,n=n,l=l,g=g), ylim=c(0,20),
         col=c('purple','lightblue','lightgreen','red','orange','yellow'),
         stats=TRUE)