RMBC
Robust Model Based Clustering
A robust clustering algorithm (Model-Based) similar to Expectation Maximization for finite mixture normal distributions is implemented, its main advantage is that the estimator is resistant to outliers, that means that results of parameter estimation are still correct when there are atypical values in the sample (see Gonzalez, Maronna, Yohai and Zamar (2021)).
- Version0.1.0
- R version≥ 3.5.0 stats
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release07/22/2021
Team
Juan Domingo Gonzalez
Victor J. Yohai
Show author detailsRolesAuthorRuben H. Zamar
Show author detailsRolesAuthorRicardo Maronna
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 169 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.
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Last 365 days
This package has been downloaded 2,249 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 Jul 23, 2024 with 33 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
- Imports3 packages
- Suggests4 packages