prabclus package overview
Description
Here is a list of the main functions in package prabclus. Most other functions are auxiliary functions for these.
Initialisation
 prabinit
Initialises presence/absence, abundance and multilocus data with dominant markers for use with most other key prabclusfunctions.
 alleleinit
Initialises multilocus data with codominant markers for use with key prabclusfunctions.
 alleleconvert
Generates the input format required by
alleleinit
.
Tests for clustering and nestedness
 prabtest

Computes the tests introduced in Hausdorf and Hennig (2003) and Hennig and Hausdorf (2004; these tests occur in some further publications of ours but this one is the most detailed statistical reference) for presence/absence data. Allows use of the gecodissimilarity (Hennig and Hausdorf, 2006).
 abundtest

Computes the test introduced in Hausdorf and Hennig (2007) for abundance data.
 homogen.test
A classical distancebased test for homogeneity going back to Erdos and Renyi (1960) and Ling (1973).
Clustering
 prabclust
Species clustering for biotic element analysis (Hausdorf and Hennig, 2007, Hennig and Hausdorf, 2004 and others), clustering of individuals for species delimitation (Hausdorf and Hennig, 2010) based on Gaussian mixture model clustering with noise as implemented in Rpackage
mclust
, Fraley and Raftery (1998), on output of multidimensional scaling from distances as computed byprabinit
oralleleinit
. See alsostressvals
for help with choosing the number of MDSdimensions. hprabclust
An unpublished alternative to
prabclust
using hierarchical clustering methods. lociplots
Visualisation of clusters of genetic markers vs. clusters of species.
 NNclean
Nearest neighbor based classification of observations as noise/outliers according to Byers and Raftery (1998).
Dissimilarity matrices
 alleledist
Shared allele distance (see the corresponding help pages for references).
 dicedist
Dice distance.
 geco
geco coefficient, taking geographical distance into account.
 jaccard
Jaccard distance.
 kulczynski
Kulczynski dissimilarity.
 qkulczynski
Quantitative Kulczynski dissimilarity for abundance data.
Small conversion functions
 coord2dist
Computes geographical distances from geographical coordinates.
 geo2neighbor
Computes a neighborhood list from geographical distances.
 alleleconvert
A somewhat restricted function for conversion of different file formats used for genetic data with codominant markers.
Data sets
kykladspecreg
, siskiyou
,
veronica
, tetragonula
.
Author(s)
Christian Hennig chrish@stats.ucl.ac.uk http://www.homepages.ucl.ac.uk/~ucakche/
References
Byers, S. and Raftery, A. E. (1998) NearestNeighbor Clutter Removal for Estimating Features in Spatial Point Processes, Journal of the American Statistical Association, 93, 577584.
Erdos, P. and Renyi, A. (1960) On the evolution of random graphs. Publications of the Mathematical Institute of the Hungarian Academy of Sciences 5, 1761.
Fraley, C. and Raftery, A. E. (1998) How many clusters? Which clusterin method?  Answers via ModelBased Cluster Analysis. Computer Journal 41, 578588.
Hausdorf, B. and Hennig, C. (2003) Nestedness of northwest European land snail ranges as a consequence of differential immigration from Pleistocene glacial refuges. Oecologia 135, 102109.
Hausdorf, B. and Hennig, C. (2007) Null model tests of clustering of species, negative cooccurrence patterns and nestedness in metacommunities. Oikos 116, 818828.
Hausdorf, B. and Hennig, C. (2010) Species Delimitation Using Dominant and Codominant Multilocus Markers. Systematic Biology, 59, 491503.
Hennig, C. and Hausdorf, B. (2004) Distancebased parametric bootstrap tests for clustering of species ranges. Computational Statistics and Data Analysis 45, 875896.
Hennig, C. and Hausdorf, B. (2006) A robust distance coefficient between distribution areas incorporating geographic distances. Systematic Biology 55, 170175.
Ling, R. F. (1973) A probability theory of cluster analysis. Journal of the American Statistical Association 68, 159164.