most citedBiarchetype analysis for univariate functional data. An application to macroeconomic financial time series

1 citations · 2 across the 2 of their papers we have counts for

collaborators

7 papers

stat.ME20261 cited

Biarchetype analysis for univariate functional data. An application to macroeconomic financial time series

Aleix Alcacer, Rafael Benitez, Vicente J. Bolos +1

We introduce biarchetype analysis for the first time in the context of univariate functional data. This unsupervised methodology extends archetype analysis by simultaneously identi…

stat.ME20261 cited

Archetypal analysis of European 10-year government bond yields with multidimensional scaling of two-mode three-way asymmetric dissimilarities

Aleix Alcacer, Rafael Benitez, Vicente J. Bolos +1

A recent methodology for extracting archetypal profiles from three-way asymmetric proximity data is applied to a dataset comprising 23 x 23 x 3 two-mode, three-way asymmetric dissi…

stat.AP2026

Representing asymmetric relationships by h-plots. Discovering the archetypal patterns of cross-journal citation relationships

Aleix Alcacer, Irene Epifanio

This work approaches the multidimensional scaling problem from a novel angle. We introduce a scalable method based on the h-plot, which inherently accommodates asymmetric proximity…

stat.ME2026

Archetypal cases for questionnaires with nominal multiple choice questions

Aleix Alcacer, Irene Epifanio

Archetypal analysis serves as an exploratory tool that interprets a collection of observations as convex combinations of pure (extreme) patterns. When these patterns correspond to…

stat.ME2025

A Survey on Archetypal Analysis

Aleix Alcacer, Irene Epifanio, Sebastian Mair +1

Archetypal analysis (AA) was originally proposed in 1994 by Adele Cutler and Leo Breiman as a computational procedure for extracting distinct aspects, so-called archetypes, from ob…

stat.ME2025

Multidimensional scaling of two-mode three-way asymmetric dissimilarities: finding archetypal profiles and clustering

Aleix Alcacer, Rafael Benitez, Vicente J. Bolos +1

Multidimensional scaling visualizes dissimilarities among objects and reduces data dimensionality. While many methods address symmetric proximity data, asymmetric and especially th…