| hist {graphics} | R Documentation |
The generic function hist computes a histogram of the given
data values. If plot=TRUE, the resulting object of
class "histogram" is plotted by
plot.histogram, before it is returned.
hist(x, ...)
## Default S3 method:
hist(x, breaks = "Sturges", freq = NULL, probability = !freq,
include.lowest = TRUE, right = TRUE,
density = NULL, angle = 45, col = NULL, border = NULL,
main = paste("Histogram of" , xname),
xlim = range(breaks), ylim = NULL,
xlab = xname, ylab,
axes = TRUE, plot = TRUE, labels = FALSE,
nclass = NULL, ...)
x |
a vector of values for which the histogram is desired. |
breaks |
one of:
|
freq |
logical; if TRUE, the histogram graphic is a
representation of frequencies, the counts component of
the result; if FALSE, probability densities, component
density, are plotted (so that the histogram has a total area
of one). Defaults to TRUE iff breaks are
equidistant (and probability is not specified). |
probability |
an alias for !freq, for S compatibility. |
include.lowest |
logical; if TRUE, an x[i] equal to
the breaks value will be included in the first (or last, for
right = FALSE) bar. This will be ignored (with a warning)
unless breaks is a vector. |
right |
logical; if TRUE, the histograms cells are
right-closed (left open) intervals. |
density |
the density of shading lines, in lines per inch.
The default value of NULL means that no shading lines
are drawn. Non-positive values of density also inhibit the
drawing of shading lines. |
angle |
the slope of shading lines, given as an angle in degrees (counter-clockwise). |
col |
a colour to be used to fill the bars.
The default of NULL yields unfilled bars. |
border |
the color of the border around the bars. The default is to use the standard foreground color. |
main, xlab, ylab |
these arguments to title have useful
defaults here. |
xlim, ylim |
the range of x and y values with sensible defaults.
Note that xlim is not used to define the histogram (breaks),
but only for plotting (when plot = TRUE). |
axes |
logical. If TRUE (default), axes are draw if the
plot is drawn. |
plot |
logical. If TRUE (default), a histogram is
plotted, otherwise a list of breaks and counts is returned. In the
latter case, a warning is used if (typically graphical) arguments
are specified that only apply to the plot = TRUE case. |
labels |
logical or character. Additionally draw labels on top
of bars, if not FALSE; see plot.histogram. |
nclass |
numeric (integer). For S(-PLUS) compatibility only,
nclass is equivalent to breaks for a scalar or
character argument. |
... |
further graphical parameters passed to
plot.histogram and their to title and
axis (if plot=TRUE). |
The definition of “histogram” differs by source (with
country-specific biases). R's default with equi-spaced breaks (also
the default) is to plot the counts in the cells defined by
breaks. Thus the height of a rectangle is proportional to
the number of points falling into the cell, as is the area
provided the breaks are equally-spaced.
The default with non-equi-spaced breaks is to give a plot of area one, in which the area of the rectangles is the fraction of the data points falling in the cells.
If right = TRUE (default), the histogram cells are intervals
of the form (a, b], i.e., they include their right-hand endpoint,
but not their left one, with the exception of the first cell when
include.lowest is TRUE.
For right = FALSE, the intervals are of the form [a, b),
and include.lowest really has the meaning of
“include highest”.
A numerical tolerance of 1e-7 times the median bin size is applied when counting entries on the edges of bins.
The default for breaks is "Sturges": see
nclass.Sturges. Other names for which algorithms
are supplied are "Scott" and "FD" /
"Freedman-Diaconis" (with corresponding functions
nclass.scott and nclass.FD).
Case is ignored and partial matching is used.
Alternatively, a function can be supplied which
will compute the intended number of breaks as a function of x.
an object of class "histogram" which is a list with components:
breaks |
the n+1 cell boundaries (= breaks if that
was a vector). |
counts |
n integers; for each cell, the number of
x[] inside. |
density |
values f^(x[i]), as estimated
density values. If all(diff(breaks) == 1), they are the
relative frequencies counts/n and in general satisfy
sum[i; f^(x[i])
(b[i+1]-b[i])] = 1, where b[i] = breaks[i]. |
intensities |
same as density. Deprecated, but retained
for compatibility. |
mids |
the n cell midpoints. |
xname |
a character string with the actual x argument name. |
equidist |
logical, indicating if the distances between
breaks are all the same. |
The resulting value does not depend on the values of
the arguments freq (or probability)
or plot. This is intentionally different from S.
Prior to R 1.7.0, the element breaks of the result was
adjusted for numerical tolerances. The nominal values are now
returned even though tolerances are still used when counting.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
Venables, W. N. and Ripley. B. D. (2002) Modern Applied Statistics with S. Springer.
nclass.Sturges, stem,
density, truehist in package MASS.
Typical plots with vertical bars are not histograms. Consider
barplot or plot(*, type = "h")
for such bar plots.
op <- par(mfrow=c(2, 2))
hist(islands)
utils::str(hist(islands, col="gray", labels = TRUE))
hist(sqrt(islands), br = 12, col="lightblue", border="pink")
##-- For non-equidistant breaks, counts should NOT be graphed unscaled:
r <- hist(sqrt(islands), br = c(4*0:5, 10*3:5, 70, 100, 140), col='blue1')
text(r$mids, r$density, r$counts, adj=c(.5, -.5), col='blue3')
sapply(r[2:3], sum)
sum(r$density * diff(r$breaks)) # == 1
lines(r, lty = 3, border = "purple") # -> lines.histogram(*)
par(op)
utils::str(hist(islands, br=12, plot= FALSE)) #-> 10 (~= 12) breaks
utils::str(hist(islands, br=c(12,20,36,80,200,1000,17000), plot = FALSE))
hist(islands, br=c(12,20,36,80,200,1000,17000), freq = TRUE,
main = "WRONG histogram") # and warning
set.seed(14)
x <- rchisq(100, df = 4)
## Comparing data with a model distribution should be done with qqplot()!
qqplot(x, qchisq(ppoints(x), df = 4)); abline(0,1, col = 2, lty = 2)
## if you really insist on using hist() ... :
hist(x, freq = FALSE, ylim = c(0, 0.2))
curve(dchisq(x, df = 4), col = 2, lty = 2, lwd = 2, add = TRUE)