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.

Version: 0.2.4
Imports: Rcpp (≥ 0.12.13), MixSim, mclust, stats, lowmemtkmeans
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, ggplot2
Published: 2019-06-29
Author: Andrew T. Jones, Hien D. Nguyen
Maintainer: Andrew T. Jones <andrewthomasjones at>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: SAGMM results


Reference manual: SAGMM.pdf
Package source: SAGMM_0.2.4.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SAGMM_0.2.4.tgz, r-release (x86_64): SAGMM_0.2.4.tgz, r-oldrel: SAGMM_0.2.4.tgz
Old sources: SAGMM archive


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