histogram(formula,
data,
type = c("percent", "count", "density"),
nint = if(is.factor(x)) length(levels(x))
else round(log2(length(x))+1),
endpoints = range(x[!na.x]),
breaks = if(is.factor(x)) seq(0.5, length = length(levels(x))
+ 1) else do.breaks(endpoints, nint),
equal.widths = FALSE,
...)
densityplot(formula, data, n = 50, plot.points = TRUE, ref = FALSE,
...)
do.breaks(endpoints, nint)
~ x | g1 * g2 * ...
indicates that histograms or Kernel Density estimates of x
should be produced conditioned on the levels of the (optional)
variables g1,g2,...
. When the conditionibreaks
is unspecified in
the call.breaks
is
unspecified. In do.breaks
, this specifies the interval that
is to be divided up.type
that makes sense
is density.Usually all panels use the same brea
breaks=NULL
.
If TRUE
, equally spaced bins will be selected, otherwise,
approximately equal area bins will be selected (this would mean that
the breakpoints will not be equally spacex
values
should be plotted along the y=0
line.densityplot
, if the default panel function is
used, then arguments appropriate to density
can be
included. This can control the details of how the Kehistogram
draws Conditional Histograms, while
densityplot
draws Conditional Kernel Density Plots. The
density estimate in densityplot
is actually calculated using
the function density
, and all arguments accepted by it can be
passed (as ...
) in the call to densityplot
to control
the output. See documentation of density
for details. (Note:
The default value of the argument n
of density
is
changed to 50.)
These and all other high level Trellis functions have several
arguments in common. These are extensively documented only in the
help page for xyplot
, which should be consulted to learn more
detailed usage. do.breaks
is an utility function that calculates breakpoints
given an interval and the number of pieces to break it into.
xyplot
,
panel.histogram
,
density
,
panel.densityplot
,
panel.mathdensity
,
Lattice
require(stats)
histogram( ~ height | voice.part, data = singer, nint = 17,
endpoints = c(59.5, 76.5), layout = c(2,4), aspect = 1,
xlab = "Height (inches)")
histogram( ~ height | voice.part, data = singer,
xlab = "Height (inches)", type = "density",
panel = function(x, ...) {
panel.histogram(x, ...)
panel.mathdensity(dmath = dnorm, col = "black",
args = list(mean=mean(x),sd=sd(x)))
} )
densityplot( ~ height | voice.part, data = singer, layout = c(2, 4),
xlab = "Height (inches)", bw = 5)
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