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)
<arxiv:1906.08198>).