emstreeR: Tools for Fast Computing and Plotting Euclidean Minimum Spanning Trees

Fast and easily computes an Euclidean Minimum Spanning Tree (EMST) from data. This package relies on 'RcppMLPACK' to provide an R interface to the Dual-Tree Boruvka algorithm (March, Ram, Gray, 2010, <doi:10.1145/1835804.1835882>) implemented in 'mlpack', the C++ Machine Learning Library (Curtin et. al., 2013). The Dual-Tree Boruvka is theoretically and empirically the fastest algorithm for computing an EMST. This package also provides functions and an S3 method for readily plotting Minimum Spanning Trees (MST) using either the style of the 'base', 'scatterplot3d', or 'ggplot2' libraries.

Version: 2.2.2
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 0.12.18), scatterplot3d, ggplot2, BBmisc
LinkingTo: Rcpp, RcppMLPACK, RcppArmadillo, BH
Published: 2020-11-30
Author: Allan Quadros [aut, cre]
Maintainer: Allan Quadros <allanvcq at gmail.com>
BugReports: https://github.com/allanvc/emstreeR/issues/
License: BSD_3_clause + file LICENSE
NeedsCompilation: yes
SystemRequirements: C++11 compiler.
Materials: README
CRAN checks: emstreeR results


Reference manual: emstreeR.pdf
Package source: emstreeR_2.2.2.tar.gz
Windows binaries: r-devel: emstreeR_2.2.2.zip, r-release: emstreeR_2.2.2.zip, r-oldrel: emstreeR_2.2.2.zip
macOS binaries: r-release: emstreeR_2.2.2.tgz, r-oldrel: emstreeR_2.2.2.tgz
Old sources: emstreeR archive

Reverse dependencies:

Reverse imports: KPC, wflo


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