

   AAdddd ``JJiitttteerr'' ((NNooiissee)) ttoo NNuummbbeerrss

        jitter(x, factor=1, amount = NULL)

   DDeessccrriippttiioonn::

        `jitter(x,...)' returns a numeric of the same length as
        `x', but with an `amount' of noise added in order to
        break ties. The result, say `r', is `r <- x + runif(n,
        -a, a)' where `n <- length(x)' and `a' is the `amount'
        argument (if specified).

   DDeettaaiillss::

        Let `z <- max(x) - min(x)' (assuming the usual case).
        The amount `a' to be added is either provided as posi-
        tive argument `amount' or otherwise computed from `z',
        as follows:

        If `amount == 0', we set `a <- factor * z/50' (same as
        S).

        If `amount' is `NULL' (default), we set `a <- factor *
        d/5' where d is the smallest difference between adja-
        cent unique (apart from fuzz) `x' values.

   AAuutthhoorr((ss))::

        Werner Stahel and Martin Maechler, ETH Zurich

   RReeffeerreenncceess::

        Chambers, J.M., Cleveland, W.~S., Kleiner, B. and
        Tukey, P.A. (1983).  Graphical Methods for Data Analy-
        sis, Wadsworth; figures 2.8, 4.22, 5.4.

   SSeeee AAllssoo::

        `rug' which you may want to combine with `jitter'.

   EExxaammpplleess::

        round(jitter(c(rep(1,3),  rep(1.2, 4), rep(3,3))), 3)
        ## These two `fail' with S-plus 3.x:
        jitter(rep(0, 7))
        jitter(rep(10000,5))

