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",  ...)

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 the plot function: the title main be changed with main=, the axis labels with xlab =, and ylab =, and so on.


z.statthe $Z$-statistic (sum of rows*columns of lower triangle) of the data matrices.p$P$-value (quantile of the observed $Z$-statistic in the permutation distribution).alternativethe alternative hypothesis.


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")
Documentation reproduced from package ape, version 3.0-2, License: GPL (>= 2)

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