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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.

Versions across snapshots

VersionRepositoryFileSize
0.2.5 rolling linux/jammy R-4.5 SAGMM_0.2.5.tar.gz 79.2 KiB
0.2.5 rolling linux/noble R-4.5 SAGMM_0.2.5.tar.gz 79.8 KiB
0.2.5 rolling source/ R- SAGMM_0.2.5.tar.gz 7.0 KiB
0.2.5 latest linux/jammy R-4.5 SAGMM_0.2.5.tar.gz 79.2 KiB
0.2.5 latest linux/noble R-4.5 SAGMM_0.2.5.tar.gz 79.8 KiB
0.2.5 latest source/ R- SAGMM_0.2.5.tar.gz 7.0 KiB
0.2.5 2026-04-26 source/ R- SAGMM_0.2.5.tar.gz 7.0 KiB
0.2.5 2026-04-23 source/ R- SAGMM_0.2.5.tar.gz 7.0 KiB
0.2.5 2026-04-09 windows/windows R-4.5 SAGMM_0.2.5.zip 490.2 KiB
0.2.4 2025-04-20 source/ R- SAGMM_0.2.4.tar.gz 15.2 KiB

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