histogram(x, data, ...)
densityplot(x, data, ...)
"histogram"(x, data, allow.multiple, outer = TRUE, auto.key = FALSE, aspect = "fill", panel = lattice.getOption("panel.histogram"), prepanel, scales, strip, groups, xlab, xlim, ylab, ylim, type = c("percent", "count", "density"), nint = if (is.factor(x)) nlevels(x) else round(log2(length(x)) + 1), endpoints = extend.limits(range(as.numeric(x), finite = TRUE), prop = 0.04), breaks, equal.widths = TRUE, drop.unused.levels = lattice.getOption("drop.unused.levels"), ..., lattice.options = NULL, default.scales = list(), default.prepanel = lattice.getOption("prepanel.default.histogram"), subscripts, subset)
"histogram"(x, data = NULL, xlab, ...)
"histogram"(x, data = NULL, xlab, ...)
"densityplot"(x, data, allow.multiple = is.null(groups) || outer, outer = !is.null(groups), auto.key = FALSE, aspect = "fill", panel = lattice.getOption("panel.densityplot"), prepanel, scales, strip, groups, weights, xlab, xlim, ylab, ylim, bw, adjust, kernel, window, width, give.Rkern, n = 50, from, to, cut, na.rm, drop.unused.levels = lattice.getOption("drop.unused.levels"), ..., lattice.options = NULL, default.scales = list(), default.prepanel = lattice.getOption("prepanel.default.densityplot"), subscripts, subset)
"densityplot"(x, data = NULL, xlab, ...)
do.breaks(endpoints, nint)formula method, x can be a formula of the form
~ x | g1 * g2 * ..., indicating that histograms or kernel
density estimates of the x variable should be produced
conditioned on the levels of the (optional) variables g1,
g2, .... x should be numeric (or possibly a factor
in the case of histogram), and each of g1, g2,
... should be either factors or shingles.
As a special case, the right hand side of the formula can contain
more than one term separated by ‘+’ signs (e.g., ~ x1 +
x2 | g1 * g2). What happens in this case is described in the
documentation for xyplot. Note that in either form,
all the terms in the formula must have the same length after
evaluation.
For the numeric and factor methods, x is the
variable whose histogram or Kernel density estimate is drawn.
Conditioning is not allowed in these cases.
formula method, an optional data source (usually a
data frame) in which variables are to be evaluated (see
xyplot for details). data should not be
specified for the other methods, and is ignored with a warning if it
is.
"percent" and "count" give relative frequency
and frequency histograms respectively, and can be misleading when
breakpoints are not equally spaced. "density" produces a
density histogram. type defaults to "density" when the breakpoints are
unequally spaced, and when breaks is NULL or a
function, and to "percent" otherwise.
breaks is unspecified or NULL in the call.
Ignored when the variable being plotted is a factor.
breaks is unspecified and the variable being plotted is not a
factor. In do.breaks, this specifies the interval that is to
be divided up.
type that makes sense is density. When breaks is unspecified, the value of
lattice.getOption("histogram.breaks") is first checked. If
this value is NULL, then the default is to use
breaks = seq_len(1 + nlevels(x)) - 0.5
when x is a factor, and
breaks = do.breaks(endpoints, nint)
otherwise. Breakpoints calculated in such a manner are used in all
panels. If the retrieved value is not NULL, or if
breaks is explicitly specified, it affects the display in
each panel independently. Valid values are those accepted as the
breaks argument in hist. In particular, this
allows specification of breaks as an integer giving the
number of bins (similar to nint), as a character string
denoting a method, or as a function. When specified explicitly, a special value of breaks is
NULL, in which case the number of bins is determined by
nint and then breakpoints are chosen according to the value
of equal.widths.
breaks=NULL. If
TRUE, equally spaced bins will be selected, otherwise,
approximately equal area bins will be selected (typically producing
unequally spaced breakpoints).
density.
panel.histogram and
panel.densityplot are documented separately, and have
arguments that can be used to customize its output in various ways.
Such arguments can usually be directly supplied to the high-level
function.
xyplot. xyplot. xyplot. xyplot. xyplot. xyplot. xyplot. Note that the default panel function for
histogram does not support grouped displays, whereas the one
for densityplot does.
xyplot. xyplot. xyplot. xyplot. xyplot. xyplot. xyplot. xyplot.
groups and terms in the formula, if any. If this is
specified, it is subsetted using subscripts inside the panel
function to match it to the corresponding x values. At the time of writing, weights do not work in conjunction
with an extended formula specification (this is not too hard to fix,
so just bug the maintainer if you need this feature).
density.
density.
density.
This argument is made available only for ease of implementation, and
will produce an error if TRUE.
density.
NA values should be ignored.
Passed on as argument to density, but unlike in
density, the default is TRUE.
xyplot for non-trivial details. histogram draws Conditional Histograms, and densityplot
draws Conditional Kernel Density Plots. The default panel function
uses the density function to compute the density
estimate, and all arguments accepted by density can be
specified in the call to densityplot to control the output.
See documentation of density for details. Note that 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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