vwstrip {denstrip} | R Documentation |
Varying-width strips
Description
Varying-width strips give a compact illustration of a distribution. The width of the strip is proportional to the density. This function adds a varying-width strip to an exising plot.
Usage
vwstrip(x, dens, at, width, horiz=TRUE, scale=1, limits=c(-Inf, Inf),
col="gray", border=NULL, lwd, lty, ticks=NULL, tlen=1, twd, tty,
lattice=FALSE,...)
panel.vwstrip(...)
Arguments
x |
Either the vector of points at which the density is
evaluated (if |
dens |
Density at |
at |
Position of the centre of the strip on the y-axis (if
|
width |
Thickness of the strip at the maximum density, that is, the length of its shorter dimension. Defaults to 1/20 of the axis range. |
horiz |
Draw the strip horizontally ( |
scale |
Alternative way of specifying the thickness of the
strip, as a proportion of |
limits |
Vector of minimum and maximum values, respectively, at which to terminate the strip. |
col |
Colour to shade the strip, either as a built-in R
colour name (one of |
border |
Colour of the border, see |
lwd |
Line width of the border (defaults to
|
lty |
Line type of the border (defaults to
|
ticks |
Vector of |
tlen |
Length of the ticks, relative to the thickness of the strip. |
twd |
Line width of these marks (defaults to
|
tty |
Line type of these marks (defaults to
|
lattice |
Set this to |
... |
Additional arguments supplied to |
Details
Varying-width strips look like violin plots. The difference is that
violin plots are intended to summarise data, while
vwstrip
is
intended to illustrate a distribution arising from parameter
estimation or prediction. Either the distribution is known
analytically, or an arbitrarily large sample from the distribution is
assumed to be available via a method such as MCMC or bootstrapping.
Illustrating outliers is important for summarising data, therefore
violin plots terminate at the sample minimum and maximum and superimpose
a box plot (which appears like the bridge of a violin, hence the name).
Varying-width strips, however, are used to illustrate known
distributions which may have unbounded support. Therefore it is
important to think about where the strips should terminate (the
limits
argument). For example, the end points may illustrate
a particular pair of extreme quantiles of the distribution.
The function vioplot
in the vioplot
package and panel.violin
in the lattice
package can be used to draw violin plots of observed data.
Author(s)
Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>
References
Jackson, C. H. (2008) Displaying uncertainty with shading. The American Statistician, 62(4):340-347.
Hintze, J.L. and Nelson, R.D. (1998) Violin plots: a box plot - density trace synergism. The American Statistician 52(2),181–184.
See Also
Examples
x <- seq(-4, 4, length=10000)
dens <- dnorm(x)
plot(x, xlim=c(-5, 5), ylim=c(-5, 5), xlab="x", ylab="x", type="n")
vwstrip(x, dens, at=1, ticks=qnorm(c(0.025, 0.25,0.5, 0.75, 0.975)))
## Terminate the strip at specific outer quantiles
vwstrip(x, dens, at=2, limits=qnorm(c(0.025, 0.975)))
vwstrip(x, dens, at=3, limits=qnorm(c(0.005, 0.995)))
## Compare with density strip
denstrip(x, dens, at=0)
## Estimate the density from a large sample
x <- rnorm(10000)
vwstrip(x, at=4)