Package: AMDconfigurations 0.1.0
AMDconfigurations: Geometric Analysis of Configurations in High-Dimensional Spaces
Tools for analysing the geometry of configurations in high-dimensional spaces using the Average Membership Degree (AMD) framework and synthetic configuration generation. The package supports a domain-agnostic approach to studying the shape, dispersion, and internal structure of point clouds, with applications across biological and ecological datasets, including those derived from deep-time records. The AMD framework builds on the idea that strongly coupled systems may occupy a limited set of recurrent regimes in state space, producing high-occupancy regions separated by sparsely populated transitional configurations. The package focuses on detecting these concentration patterns and quantifying their geometric definition without assuming any underlying dynamical model. It provides AMD curve computation, cluster assignment, and sigma-equivalent estimation, together with S3 methods for plotting, printing, and summarising AMD and sigma-equivalent objects. Mendoza (2025) <https://mmendoza1967.github.io/AMDconfigurations/>.
Authors:
AMDconfigurations_0.1.0.tar.gz
AMDconfigurations_0.1.0.zip(r-4.7)AMDconfigurations_0.1.0.zip(r-4.6)AMDconfigurations_0.1.0.zip(r-4.5)
AMDconfigurations_0.1.0.tgz(r-4.6-any)AMDconfigurations_0.1.0.tgz(r-4.5-any)
AMDconfigurations_0.1.0.tar.gz(r-4.7-any)AMDconfigurations_0.1.0.tar.gz(r-4.6-any)
AMDconfigurations_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
AMDconfigurations/json (API)
| # Install 'AMDconfigurations' in R: |
| install.packages('AMDconfigurations', repos = c('https://mmendoza1967.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mmendoza1967/amdconfigurations/issues
Pkgdown/docs site:https://mmendoza1967.github.io
Last updated from:7464478610. Checks:7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | WARNING | 113 | ||
| source / vignettes | OK | 178 | ||
| linux-release-x86_64 | WARNING | 109 | ||
| macos-release-arm64 | WARNING | 127 | ||
| macos-oldrel-arm64 | WARNING | 144 | ||
| windows-devel | WARNING | 67 | ||
| windows-release | WARNING | 66 | ||
| windows-oldrel | WARNING | 78 | ||
| wasm-release | OK | 104 |
Exports:assign_clusters_bestcompute_amd_curvecreate_synthetic_samplesestimate_sigma_equivalent
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Select the best fuzzy c-means partition across repeated initialisations | assign_clusters_best |
| Compute the AMD curve across a range of cluster numbers | compute_amd_curve |
| Generate synthetic clustered samples with isotropic Gaussian noise | create_synthetic_samples |
| Estimate the sigma-equivalent compactness of a dataset | estimate_sigma_equivalent |
