Package: gmfd 1.0.1
gmfd: Inference and Clustering of Functional Data
Some methods for the inference and clustering of univariate and multivariate functional data, using a generalization of Mahalanobis distance, along with some functions useful for the analysis of functional data. For further details, see Martino A., Ghiglietti, A., Ieva, F. and Paganoni A. M. (2017) <arxiv:1708.00386>.
Authors:
gmfd_1.0.1.tar.gz
gmfd_1.0.1.zip(r-4.5)gmfd_1.0.1.zip(r-4.4)gmfd_1.0.1.zip(r-4.3)
gmfd_1.0.1.tgz(r-4.4-any)gmfd_1.0.1.tgz(r-4.3-any)
gmfd_1.0.1.tar.gz(r-4.5-noble)gmfd_1.0.1.tar.gz(r-4.4-noble)
gmfd_1.0.1.tgz(r-4.4-emscripten)gmfd_1.0.1.tgz(r-4.3-emscripten)
gmfd.pdf |gmfd.html✨
gmfd/json (API)
| # Install 'gmfd' in R: |
| install.packages('gmfd', repos = c('https://martinoandrea92.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:acde000eb7. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 14 2024 |
| R-4.5-win | OK | Sep 14 2024 |
| R-4.5-linux | OK | Sep 14 2024 |
| R-4.4-win | OK | Sep 14 2024 |
| R-4.4-mac | OK | Sep 14 2024 |
| R-4.3-win | OK | Sep 14 2024 |
| R-4.3-mac | OK | Sep 14 2024 |
Exports:funDatafunDistgmfd_dissgmfd_kmeansgmfd_simulategmfd_test
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| 'S3' Class for functional datasets. A class for univariate or multivariate functional dataset. | funData |
| Distance function | funDist |
| Dissimilarity matrix function | gmfd_diss |
| k-means clustering algorithm | gmfd_kmeans |
| Simulation of a functional sample | gmfd_simulate |
| Two-sample hypotesis tests | gmfd_test |
| A method to plot 'funData' objects | plot.funData |
