SAGMM
0.2.5Clustering via Stochastic Approximation and Gaussian Mixture Models
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 50%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.2.5Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.2.42019-06-29 · diff ↗
- 0.2.32019-05-09
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-05-09
- Total releases
- 3 / 7 yrs
- License
- GPL-3 OSI
- Download size
- 7.1 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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Run in R for the authors' preferred citation:
citation("SAGMM")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
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