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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:988daa6342. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-linux-x86_64 | OK | Nov 20 2024 |
Exports:entropyentropy.fdfdframegmdepthgmdepth.fdkmdepth.fdlevelsetdistrkhs
Dependencies:DEoptimRFNNlatticeMASSmvtnormpcaPPpdistrobustbaserrcov
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Australian Male Mortality Rates | Ausmale |
| Entropy Computation | entropy |
| Functional Entropy Measures | entropy.fd |
| Functional Data Frame | fdframe fdframe.default |
| Generalized Mahalanobis Depth and Distance | gmdepth |
| Generalized Mahalanobis Kernel Depth and Distance for Functional Data | gmdepth.fd |
| Kernel Mahalanobis Depth for Functional Data | kmdepth.fd |
| Level Set Distances | levelsetdist |
| Merval Index | merval |
| RKHS Representation | rkhs |