ktaucenters
Robust Clustering Procedures
A clustering algorithm similar to K-Means is implemented, it has two main advantages, namely (a) The estimator is resistant to outliers, that means that results of estimator are still correct when there are atypical values in the sample and (b) The estimator is efficient, roughly speaking, if there are no outliers in the sample, results will be similar to those obtained by a classic algorithm (K-Means). Clustering procedure is carried out by minimizing the overall robust scale so-called tau scale. (see Gonzalez, Yohai and Zamar (2019)
- Version1.0.0
- R version≥ 2.10
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Languageen-US
- Last release01/16/2024
Documentation
Team
Juan Domingo Gonzalez
Victor J. Yohai
Show author detailsRolesAuthorRuben H. Zamar
Show author detailsRolesAuthorDouglas Alberto Carmona Guanipa
Show author detailsRolesAuthor
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- Depends4 packages
- Imports1 package
- Suggests5 packages
- Linking To1 package
- Reverse Imports1 package