Clustering Algorithms

Michael Wester (wester@math.unm.edu)
SpatioTemporal Modeling Center
University of New Mexico Health Sciences Center

Clustering, PairCorr, SimulateDomains, SRcluster are a set of MATLAB classes
that
o collect together various spatial clustering statistics and algorithms
  (hierarchal, DBSCAN [4 versions], Getis based, Voronoi based);
o pair auto- and cross-correlation curves and statistics
o simulations of spatial domains (clusters) of fluorophore localizations that
  exhibit distributions of observations representing blinks; and 
o a top-down clustering algorithm to collapse clusters of observations of
  blinking fluorophores into a single estimate of the true location of the
  fluorophore using a log-likelihood hypothesis test (H-SET: Hierarchical
  Single Emitter Hypothesis Test).
Many of these algorithms operate in 3D as well as 2D.  I will also demonstrate
SuperCluster, which provides a GUI interface to some of the above.

Please download MATLAB Clustering Classes Version 1, SuperCluster (and the
DERIVEST Suite) from the links on

   http://stmc.health.unm.edu/tools-and-data/