Package: bigdatadist 1.1

Gabriel Martos

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).

Authors:Gabriel Martos [aut, cre], Nicolas Hernandez [aut]

bigdatadist_1.1.tar.gz
bigdatadist_1.1.tar.gz(r-4.5-noble)bigdatadist_1.1.tar.gz(r-4.4-noble)
bigdatadist_1.1.tgz(r-4.4-emscripten)bigdatadist_1.1.tgz(r-4.3-emscripten)
bigdatadist.pdf |bigdatadist.html
bigdatadist/json (API)

# Install 'bigdatadist' in R:
install.packages('bigdatadist', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

fortran

1.00 score 195 downloads 8 exports 9 dependencies

Last updated 7 years agofrom:988daa6342. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 20 2025
R-4.5-linux-x86_64OKMar 20 2025
R-4.4-linux-x86_64OKMar 20 2025

Exports:entropyentropy.fdfdframegmdepthgmdepth.fdkmdepth.fdlevelsetdistrkhs

Dependencies:DEoptimRFNNlatticeMASSmvtnormpcaPPpdistrobustbaserrcov