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, …)# S3 method for default
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, warn.unused = TRUE, …)
a vector of values for which the histogram is desired.
one of:
a vector giving the breakpoints between histogram cells,
a function to compute the vector of breakpoints,
a single number giving the number of cells for the histogram,
a character string naming an algorithm to compute the number of cells (see ‘Details’),
a function to compute the number of cells.
In the last three cases the number is a suggestion only; as the
breakpoints will be set to pretty values, the number
is limited to 1e6 (with a warning if it was larger). If
breaks is a function, the x vector is supplied to it
as the only argument (and the number of breaks is only limited by
the amount of available memory).
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 if and only if breaks are
equidistant (and probability is not specified).
an alias for !freq, for S compatibility.
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.
logical; if TRUE, the histogram cells are
right-closed (left open) intervals.
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.
the slope of shading lines, given as an angle in degrees (counter-clockwise).
a colour to be used to fill the bars.
The default of NULL yields unfilled bars.
the color of the border around the bars. The default is to use the standard foreground color.
main title and axis labels: these arguments to
title() get “smart” defaults here, e.g., the default
ylab is "Frequency" iff freq is true.
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).
logical. If TRUE (default), axes are draw if the
plot is drawn.
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.
logical or character string. Additionally draw labels on top
of bars, if not FALSE; see plot.histogram.
numeric (integer). For S(-PLUS) compatibility only,
nclass is equivalent to breaks for a scalar or
character argument.
logical. If plot = FALSE and
warn.unused = TRUE, a warning will be issued when graphical
parameters are passed to hist.default().
further arguments and graphical parameters passed to
plot.histogram and thence to title and
axis (if plot = TRUE).
an object of class "histogram" which is a list with components:
the \(n+1\) cell boundaries (= breaks if that
was a vector). These are the nominal breaks, not with the boundary fuzz.
\(n\) integers; for each cell, the number of
x[] inside.
values \(\hat f(x_i)\), as estimated
density values. If all(diff(breaks) == 1), they are the
relative frequencies counts/n and in general satisfy
\(\sum_i \hat f(x_i) (b_{i+1}-b_i) = 1\), where \(b_i\) = breaks[i].
the \(n\) cell midpoints.
a character string with the actual x argument name.
logical, indicating if the distances between
breaks are all the same.
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 means ‘include highest’.
A numerical tolerance of \(10^{-7}\) times the median bin size
(for more than four bins, otherwise the median is substituted) is
applied when counting entries on the edges of bins. This is not
included in the reported breaks nor in the calculation of
density.
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 or the actual breakpoints
as a function of x.
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.
# NOT RUN {
op <- par(mfrow = c(2, 2))
hist(islands)
utils::str(hist(islands, col = "gray", labels = TRUE))
hist(sqrt(islands), breaks = 12, col = "lightblue", border = "pink")
##-- For non-equidistant breaks, counts should NOT be graphed unscaled:
r <- hist(sqrt(islands), breaks = 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$breaks)) # == 1
lines(r, lty = 3, border = "purple") # -> lines.histogram(*)
par(op)
require(utils) # for str
str(hist(islands, breaks = 12, plot = FALSE)) #-> 10 (~= 12) breaks
str(hist(islands, breaks = c(12,20,36,80,200,1000,17000), plot = FALSE))
hist(islands, breaks = c(12,20,36,80,200,1000,17000), freq = TRUE,
main = "WRONG histogram") # and warning
# }
# NOT RUN {
<!-- % save 2 seconds -->
## Extreme outliers; the "FD" rule would take very large number of 'breaks':
XXL <- c(1:9, c(-1,1)*1e300)
hh <- hist(XXL, "FD") # did not work in R <= 3.4.1; now gives warning
## pretty() determines how many counts are used (platform dependently!):
length(hh$breaks) ## typically 1 million -- though 1e6 was "a suggestion only"
# }
# NOT RUN {
require(stats)
set.seed(14)
x <- rchisq(100, df = 4)
# }
# NOT RUN {
## 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)
# }
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