Produces a spike plot of a numeric vector.
spikeplot(x, freq = FALSE, as.table = FALSE, col = par("col"),
    lty = par("lty"), lwd = par("lwd"), lend = par("lend"),
    type = "h", xlab = deparse1(substitute(x)), ylab = NULL,
    capped = FALSE, cex = sqrt(lwd) / 2, pch = 19, pcol = col, scol = NULL,
    slty = NULL, slwd = NULL, new.plot = TRUE, offset.x = 0, ymux = 1, ...)Returns invisibly table(x).
Numeric, passed into table.
Logical. If TRUE then the y-axis measures
    the frequencies, else the sample proportions.
    Intended to be as hist.
Logical.
    If TRUE then the call to plot is
    closer to plot(table(x), ...), meaning the labelling
    differs from as.table = FALSE.
    The default is to convert table(x) into a numeric
    vector which is then passed into plot
    so that the labelling is more uniform along the x-axis.
See par.
See par.
First argument is logical.
    If TRUE then the others argument are used to place
    points at the top using points
    with pcol being its colour.  
    See par.
Similar to col, lty and lwd but
    apply to some selected values.
    The input may be a named list such as
    scol = list("green" = c(2, 4, 6), "blue" = 5),
    slty = list("dashed" = c(2, 4, 6), "dotted" = 5),
    slwd = list("2" = c(2, 4, 6), "3" = 5),
    else a named vector such as
  scol = c("green" = 2, "green" = 4, "green" = 6, "blue" = 5),
  slty = c("dashed" = 2, "dashed" = 4, "dashed" = 6, "dotted" = 5),
  slwd = c("2" = 2, "2" = 4, "2" = 6, "3" = 5).
  The three arguments are ignored if as.table = TRUE.
Logical and numeric.
   Add to an existing plot? If so, set new.plot = FALSE
   and it is useful for
   the spikes to be shifted by some amount offset.x.
Numeric, y-multiplier. The response is multiplied by ymux.
  This can be useful when plotting subsets side-by-side so that
  the constituent proportions add up to the overall proportion.
Additional graphical arguments passed into an ordinary
    plot, for example,
    xlim, las, main.
T. W. Yee.
Heaping is a very commonly occurring phenomenon in
  retrospective self-reported survey data.
  Also known as digit preference data,
  it is often characterized by an excess of multiples of 10 or 5
  upon rounding.
  For this type of data
  this simple function is meant to be convenient for
  plotting the frequencies or sample proportions of
  a vector x representing a discrete random variable.
  This type of plot
  is known as a spike plot in STATA circles.
  If table(x) works then this function should hopefully
  work.
  The default for type means that any heaping and
  seeping should easily be seen. 
  If such features exist then GAITD regression is
  potentially useful---see gaitdpoisson etc.
  Currently missing values are ignored totally because
  table(x) is used without further arguments;
  this might change in the future.
if (FALSE) {
spikeplot(with(marital.nz, age), col = "pink2", lwd = 2)
}Run the code above in your browser using DataLab