Clustering and disjoint principal component analysis
Computational Statistics & Data Analysis
Finite mixtures of matrix normal distributions for classifying three-way data
Statistics and Computing
Robust clustering around regression lines with high density regions
Advances in Data Analysis and Classification
Tensor clustering via adaptive subspace iteration
Intelligent Data Analysis
Hi-index | 0.00 |
In this paper two techniques for units clustering and factorial dimensionality reduction of variables and occasions of a three-mode data set are discussed. These techniques can be seen as the simultaneous version of two procedures based on the sequential application of k-means and Tucker2 algorithms and vice versa. The two techniques, T3Clus and 3Fk-means, have been compared theoretically and empirically by a simulation study. In the latter, it has been noted that neither T3Clus nor 3Fk-means outperforms the other in every case. From these results rises the idea to combine the two techniques in a unique general model, named CT3Clus, having T3Clus and 3Fk-means as special cases. A simulation study follows to show the effectiveness of the proposal.