hist {graphics} | R Documentation |
Histograms
Description
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.
Usage
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, ...)
Arguments
x |
a vector of values for which the histogram is desired. |
breaks |
one of:
In the last three cases the number is a suggestion only. |
freq |
logical; if |
probability |
an alias for |
include.lowest |
logical; if |
right |
logical; if |
density |
the density of shading lines, in lines per inch.
The default value of |
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 |
border |
the color of the border around the bars. The default is to use the standard foreground color. |
main , xlab , ylab |
these arguments to |
xlim , ylim |
the range of x and y values with sensible defaults.
Note that |
axes |
logical. If |
plot |
logical. If |
labels |
logical or character. Additionally draw labels on top
of bars, if not |
nclass |
numeric (integer). For S(-PLUS) compatibility only,
|
... |
further graphical parameters to |
Details
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 10^{-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"
/
"Friedman-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
.
Value
an object of class "histogram"
which is a list with components:
breaks |
the |
counts |
|
density |
values |
intensities |
same as |
mids |
the |
xname |
a character string with the actual |
equidist |
logical, indicating if the distances between
|
Note
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.
References
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.
See Also
nclass.Sturges
, stem
,
density
, truehist
in package MASS.
Examples
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