emstreeR: Tools for Fast Computing and Visualizing Euclidean Minimum
Spanning Trees
Fast and easily computes an Euclidean Minimum Spanning Tree (EMST) from data,
relying on the R API for 'mlpack' - the C++ Machine Learning Library (Curtin et. al., 2013).
'emstreeR' uses the Dual-Tree Boruvka (March, Ram, Gray, 2010, <doi:10.1145/1835804.1835882>),
which is theoretically and empirically the fastest algorithm for computing an EMST. This package also provides
functions and an S3 method for readily visualizing Minimum Spanning Trees (MST) using either the
style of the 'base', 'scatterplot3d', or 'ggplot2' libraries; and functions to export the MST output to shapefiles.
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Reverse dependencies:
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