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 prabclus-functions.

alleleinit

Initialises multilocus data with codominant markers for use with key prabclus-functions.

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 geco-dissimilarity (Hennig and Hausdorf, 2006).

abundtest

Computes the test introduced in Hausdorf and Hennig (2007) for abundance data.

homogen.test

A classical distance-based 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 R-package mclust, Fraley and Raftery (1998), on output of multidimensional scaling from distances as computed by prabinit or alleleinit. See also stressvals for help with choosing the number of MDS-dimensions.

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An unpublished alternative to prabclust using hierarchical clustering methods.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) Nearest-Neighbor Clutter Removal for Estimating Features in Spatial Point Processes, Journal of the American Statistical Association, 93, 577-584.

Erdos, P. and Renyi, A. (1960) On the evolution of random graphs. Publications of the Mathematical Institute of the Hungarian Academy of Sciences 5, 17-61.

Fraley, C. and Raftery, A. E. (1998) How many clusters? Which clusterin method? - Answers via Model-Based Cluster Analysis. Computer Journal 41, 578-588.

Hausdorf, B. and Hennig, C. (2003) Nestedness of north-west European land snail ranges as a consequence of differential immigration from Pleistocene glacial refuges. Oecologia 135, 102-109.

Hausdorf, B. and Hennig, C. (2007) Null model tests of clustering of species, negative co-occurrence patterns and nestedness in meta-communities. Oikos 116, 818-828.

Hausdorf, B. and Hennig, C. (2010) Species Delimitation Using Dominant and Codominant Multilocus Markers. Systematic Biology, 59, 491-503.

Hennig, C. and Hausdorf, B. (2004) Distance-based parametric bootstrap tests for clustering of species ranges. Computational Statistics and Data Analysis 45, 875-896.

Hennig, C. and Hausdorf, B. (2006) A robust distance coefficient between distribution areas incorporating geographic distances. Systematic Biology 55, 170-175.

Ling, R. F. (1973) A probability theory of cluster analysis. Journal of the American Statistical Association 68, 159-164.

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