bigdatadist: Distances for Machine Learning and Statistics in the Context of Big Data

Functions to compute distances between probability measures or any other data object than can be posed in this way, entropy measures for samples of curves, distances and depth measures for functional data, and the Generalized Mahalanobis Kernel distance for high dimensional data. For further details about the metrics please refer to Martos et al (2014) <doi:10.3233/IDA-140706>; Martos et al (2018) <doi:10.3390/e20010033>; Hernandez et al (2018, submitted); Martos et al (2018, submitted).

Version: 1.0
Depends: R (≥ 3.4.0)
Imports: MASS, FNN, rrcov, pdist
Published: 2018-07-02
Author: Gabriel Martos [aut, cre], Nicolas Hernandez [aut]
Maintainer: Gabriel Martos <gmartos at utdt.edu>
License: GPL (≥ 3)
NeedsCompilation: yes
Citation: bigdatadist citation info
CRAN checks: bigdatadist results

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Reference manual: bigdatadist.pdf
Package source: bigdatadist_1.0.tar.gz
Windows binaries: r-devel: bigdatadist_1.0.zip, r-release: bigdatadist_1.0.zip, r-oldrel: bigdatadist_1.0.zip
OS X binaries: r-release: bigdatadist_1.0.tgz, r-oldrel: bigdatadist_1.0.tgz

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