Box-percentile strips give a compact illustration of a distribution.
The width of the strip is proportional to the probability of a more
extreme point. This function adds a box-percentile strip to an existing
plot.
Either the vector of points at which the probability is
evaluated (if prob supplied), or a sample from the distribution
(if prob not supplied).
prob
Probability, or cumulative density, of the distribution
at x. If prob is not supplied, this is estimated from
the sample x using ecdf(x).
at
Position of the centre of the strip on the y-axis (if
horiz=TRUE) or the x-axis (if horiz=FALSE).
width
Thickness of the strip at its thickest point, which will
be at the median. Defaults to 1/20 of the axis range.
horiz
Draw the strip horizontally (TRUE) or vertically (FALSE).
scale
Alternative way of specifying the thickness of the
strip, as a proportion of width.
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 colors()) or an RGB hex
value, e.g. black is "#000000".
border
Colour of the border, see polygon. Use
border=NA to show no border. The default, 'NULL', means to
use 'par("fg")' or its lattice equivalent.
lwd
Line width of the border (defaults to
par("lwd") or its lattice equivalent).
lty
Line type of the border (defaults to
par("lty") or its lattice equivalent).
ticks
Vector of x-positions on the strip to draw tick
marks, or NULL for no ticks.
tlen
Length of the ticks, relative to the thickness of the strip.
twd
Line width of these marks (defaults to
par("lwd") or its lattice equivalent).
tty
Line type of these marks (defaults to
par("lty") or its lattice equivalent).
lattice
Set this to TRUE to make bpstrip
a lattice panel function instead of a base graphics function. panel.bpstrip(x,...) is equivalent to
bpstrip(x, lattice=TRUE, ...).
...
Other arguments passed to panel.bpstrip.
Details
The box-percentile strip looks the same as the box-percentile plot
(Esty and Banfield, 2003) which is a generalisation of the boxplot for
summarising data. However, bpstrip is intended for illustrating
distributions 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.
The function bpplot in the Hmisc
package can be used to draw vertical box-percentile plots of observed
data.
Author(s)
Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>