disana {labdsv}R Documentation

Dissimilarity Analysis

Description

Dissimilarity analysis is a graphical analysis of the distribution of values in a dissimilarity matrix

Usage

disana(x)

Arguments

x an object of class ‘dist’ such as returned by dist, vegdist or dsvdis

Details

Calculates three vectors: the minimum, mean, and maximum dissimilarity for each sample in a dissimilarity matrix. By default it produces three plots: the sorted dissimilarity values, the sorted min, mean, and maximum dissimilarity for each sample, and the mean dissimilarity versus the minimum dissimilarity for each sample. Optionally, you can identify sample plots in the last panel with the mouse.

Value

Plots three graphs to the current graphical device, and returns an (invisible) list with four components:

min the minimum dissimilarity of each sample to all others
mean the mean dissimilarity of each sample to all others
max the maximum dissimilarity of each sample to all others
plots a vector of samples identified in the last panel

Note

Dissimilarity matrices are often large, and difficult to visualize directly. ‘disana’ is designed to highlight aspects of interest in these large matrices.

Author(s)

David W. Roberts droberts@montana.edu http://ecology.msu.montana.edu/droberts

References

http://ecology.msu.montana.edu/labdsv/R

Examples

    data(bryceveg) # returns a data.frame called veg
    dis.bc <- dsvdis(bryceveg,'bray/curtis')
    ## Not run: disana(dis.bc)

[Package labdsv version 1.2-1 Index]