jdgonzalezwork/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) <https://arxiv.org/abs/2102.06851>).
Getting started
Browse package contents
Package details |
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| Author | Juan Domingo Gonzalez [cre, aut], Victor J. Yohai [aut], Ruben H. Zamar [aut] Ricardo Maronna [aut] |
| Maintainer | Juan Domingo Gonzalez <juanrst@hotmail.com> |
| License | GPL (>= 2) |
| Version | 0.1.0 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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