5 delta.plot(X, k = 20, plot = TRUE, which = 1:2)
8 \item{X}{a distance matrix, may be an object of class ``dist''.}
9 \item{k}{an integer giving the number of intervals in the plot.}
10 \item{plot}{a logical specifying whether to draw the
11 \eqn{\delta}{delta} plot (the default).}
12 \item{which}{a numeric vector indicating which plots are done; 1: the
13 histogram of the \eqn{\delta_q}{delta_q} values, 2: the plot of the
14 individual \eqn{\bar{\delta}}{delta.bar} values. By default, both
18 This function makes a \eqn{\delta}{delta} plot following Holland et
22 See Holland et al. (2002) for details and interpretation.
24 The computing time of this function is proportional to the fourth
25 power of the number of observations (\eqn{O(n^4)}), so calculations
26 may be very long with only a slight increase in sample size.
29 This function returns invisibly a named list with two components:
32 \item{counts}{the counts for the histogram of
33 \eqn{\delta_q}{delta_q} values}
34 \item{delta.bar}{the mean \eqn{\delta}{delta} value for each
39 Holland, B. R., Huber, K. T., Dress, A. and Moulton, V. (2002) Delta
40 plots: a tool for analyzing phylogenetic distance data.
41 \emph{Molecular Biology and Evolution}, \bold{12}, 2051--2059.
43 \author{Emmanuel Paradis}
45 \code{\link{dist.dna}}
49 d <- dist.dna(woodmouse)
52 delta.plot(d, 40, which = 1)