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.
- Version0.2.4
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- Last release06/29/2019
Documentation
Team
Andrew T. Jones
Hien D. Nguyen
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Insights
Last 30 days
This package has been downloaded 126 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,565 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jan 22, 2025 with 26 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports4 packages
- Suggests2 packages
- Linking To2 packages