Package: SAGMM 0.2.4
Andrew T. Jones
SAGMM: Clustering via Stochastic Approximation and Gaussian Mixture Models
Computes clustering by fitting Gaussian mixture models (GMM) via stochastic approximation following the methods of Nguyen and Jones (2018) <doi:10.1201/9780429446177>. It also provides some test data generation and plotting functionality to assist with this process.
Authors:
SAGMM_0.2.4.tar.gz
SAGMM_0.2.4.tar.gz(r-4.5-noble)SAGMM_0.2.4.tar.gz(r-4.4-noble)
SAGMM_0.2.4.tgz(r-4.4-emscripten)SAGMM_0.2.4.tgz(r-4.3-emscripten)
SAGMM.pdf |SAGMM.html✨
SAGMM/json (API)
NEWS
| # Install 'SAGMM' in R: |
| install.packages('SAGMM', 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:698d3e53c3. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 14 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 14 2024 |
Exports:gainFactorsgenerateSimDataSAGMMFit
Dependencies:lowmemtkmeansMASSmclustMixSimRcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Return Gamma, a sequence of gain factors | gainFactors |
| Generate data for simulations to test the SAGMM package.. | generateSimData |
| SAGMM: A package for Clustering via Stochastic Approximation and Gaussian Mixture Models. | SAGMM-package SAGMM |
| Clustering via Stochastic Approximation and Gaussian Mixture Models (GMM) | SAGMMFit |
