hist                  package:base                  R Documentation

_H_i_s_t_o_g_r_a_m_s

_D_e_s_c_r_i_p_t_i_o_n:

     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.

_U_s_a_g_e:

     hist(x, ...)
     hist.default(x, breaks, freq = NULL, probability = !freq,
          include.lowest = TRUE,
          right = TRUE, col = NULL, border = par("fg"),
          main = paste("Histogram of" , xname),
          xlim = range(breaks), ylim = NULL,
          xlab = xname, ylab,
          axes = TRUE, plot = TRUE, labels = FALSE,
          nclass = NULL, ...)

_A_r_g_u_m_e_n_t_s:

       x: a vector of values for which the histogram is desired.

  breaks: either a single number giving the approximate number of cells
          for the histogram or a vector giving the breakpoints between
          histogram cells.

    freq: logical; if `TRUE', the histogram graphic is to present a
          representation of frequencies, i.e, the `counts' component of
          the result; if `FALSE', relative frequencies
          (``probabilities''), the `rel.freqs', are plotted.   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.

   right: logical; if `TRUE', the histograms cells are right-closed
          (left open) intervals.

     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.

main, xlab, ylab: these arguments to `title' have useful defaults here.

xlim, ylim: the range of x and y values with sensible defaults.

    plot: logical.  If `TRUE' (default), a histogram is plotted,
          otherwise a list of breaks and counts is returned.

  labels: logical or character.  Additionally draw labels on top of
          bars, if not `FALSE'; see `plot.histogram'.

  nclass: numeric (integer).  For S compatibility only, `nclass=n' is
          equivalent to `breaks=n' (n scalar).

     ...: further graphical parameters to `title' and `axis'.

_D_e_t_a_i_l_s:

     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''.

_V_a_l_u_e:

     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.

_N_o_t_e:

     The resulting value does not depend on the values of the arguments
     `freq' (or `probability') or `plot'.  This is intentionally
     different from S.

_S_e_e _A_l_s_o:

     `stem', `density'.

_E_x_a_m_p_l_e_s:

     data(islands)
     op <- par(mfrow=c(2,2))
     hist(islands)
     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)

     str(hist(islands, plot= FALSE))        #-> 5  breaks
     str(hist(islands, br=12, plot= FALSE)) #-> 10 (~= 12) breaks
     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

