histogram(formula,
          data, 
          type = c("percent", "count", "density"),
          nint = if(is.factor(x)) length(levels(x))
                 else round(log2(length(x))+1),
          endpoints = range(x[!na.x]),
          breaks = if(is.factor(x)) seq(0.5, length = length(levels(x))
          + 1) else do.breaks(endpoints, nint),
          equal.widths = FALSE, 
          ...)
densityplot(formula, data, n = 50, plot.points = TRUE, ref = FALSE,
            ...)
do.breaks(endpoints, nint)~ x | g1 * g2 * ...
    indicates that histograms or Kernel Density estimates of x
    should be produced conditioned on the levels of the (optional)
    variables g1,g2,.... When the conditionibreaks is unspecified in
    the call.breaks is
    unspecified.  In do.breaks, this specifies the interval that
    is to be divided up.type that makes sense
    is density.Usually all panels use the same brea
breaks=NULL.
    If TRUE, equally spaced bins will be selected, otherwise, 
    approximately equal area bins will be selected (this would mean that
    the breakpoints will not be equally spacex values
    should be plotted along the y=0 line.densityplot, if the default panel function is
    used, then arguments appropriate to density can be
    included. This can control the details of how the Kehistogram draws Conditional Histograms, while
  densityplot draws Conditional Kernel Density Plots.  The
  density estimate in densityplot is actually calculated using
  the function density, and all arguments accepted by it can be
  passed (as ...) in the call to densityplot to control
  the output.  See documentation of density for details. (Note:
  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,
  Latticerequire(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)Run the code above in your browser using DataLab