clusterfly http://had.co.nz/clusterfly/ Typically, there is somewhat of a divide between statistics and visualisation software. Statistics software, particularly R, provides implementation of cutting edge research methods, but limited graphics. Visualisation software will provide sophisticated visual interfaces, but few statistical algorithms. The clusterfly package presents some early experimentation aimed at overcoming this deficiency by linking R and GGobi. Cluster analysis was chosen as it is an exploratory method that needs sophisticated visualisation and statistical algorithms. Clusterfly provides some tools that work with all clustering algorithms, and some that are tailored for particular ones. Generic tools allow you to animate between clusterings (see ?cfly_animate) and produce common static graphics (?cfly_dist, ?cfly_pcp). Specific algorithms are available for: * Self organising maps (aka Kohonen neural networks), ?ggobi.som. Displays the self organising map/net in the original space of the data. * Hierarchical clustering, ?hierfly. Connects data points with lines like a dendrogram, but in the high-dimensional space of the original data * Model based clustering, ?mefly. Adds ellipsoids from the multivariate normal distributions the clusters are based on You will need GGobi (http://www.ggobi.org) and rggobi (http://www.ggobi.org/rggobi) installed to be able to use clusterfly. Regards, Hadley _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages