Mantel Test for Similarity of Two Matrices
This function computes Mantel's permutation test for similarity of two matrices. It permutes the rows and columns of the two matrices randomly and calculates a \(Z\)-statistic.
mantel.test(m1, m2, nperm = 999, graph = FALSE, alternative = "two.sided", ...)
- a numeric matrix giving a measure of pairwise distances, correlations, or similarities among observations.
- a second numeric matrix giving another measure of pairwise distances, correlations, or similarities among observations.
- the number of times to permute the data.
- a logical indicating whether to produce a summary graph (by default the graph is not plotted).
- a character string defining the alternative
"greater", or any unambiguous abbreviation of these.
- further arguments to be passed to
plot()(to add a title, change the axis labels, and so on).
The function calculates a \(Z\)-statistic for the Mantel test, equal to
the sum of the pairwise product of the lower triangles of the
permuted matrices, for each permutation of rows and columns. It
compares the permuted distribution with the \(Z\)-statistic observed
for the actual data. If
graph = TRUE, the functions plots the density estimate of
the permutation distribution along with the observed \(Z\)-statistic
as a vertical line. The
… argument allows the user to give further options to
plot function: the title main be changed with
the axis labels with
xlab =, and
ylab =, and so on.
Mantel, N. (1967) The detection of disease clustering and a generalized regression approach. Cancer Research, 27, 209--220. Manly, B. F. J. (1986) Multivariate statistical methods: a primer. London: Chapman & Hall.
q1 <- matrix(runif(36), nrow = 6) q2 <- matrix(runif(36), nrow = 6) mantel.test(q1, q2, graph = TRUE, main = "Mantel test: a random example with 6 X 6 matrices", xlab = "z-statistic", ylab = "Density", sub = "The vertical line shows the observed z-statistic")