Package: SAGMM 0.2.4
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.zip(r-4.5)SAGMM_0.2.4.zip(r-4.4)SAGMM_0.2.4.zip(r-4.3)
SAGMM_0.2.4.tgz(r-4.4-x86_64)SAGMM_0.2.4.tgz(r-4.4-arm64)SAGMM_0.2.4.tgz(r-4.3-x86_64)SAGMM_0.2.4.tgz(r-4.3-arm64)
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://andrewthomasjones.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/andrewthomasjones/sagmm/issues
Last updated 5 years agofrom:e115eb70d9. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win-x86_64 | NOTE | Oct 31 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 31 2024 |
| R-4.4-win-x86_64 | NOTE | Oct 31 2024 |
| R-4.4-mac-x86_64 | NOTE | Oct 31 2024 |
| R-4.4-mac-aarch64 | NOTE | Oct 31 2024 |
| R-4.3-win-x86_64 | NOTE | Oct 31 2024 |
| R-4.3-mac-x86_64 | NOTE | Oct 31 2024 |
| R-4.3-mac-aarch64 | NOTE | Oct 31 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 |
