23 citations · 28 across the 3 of their papers we have counts for
7 papers
A local depth measure for general data
Lucas Fernandez-Piana, Marcela Svarc
We introduce the Integrated Dual Local Depth which is a local depth measure for data in a Banach space based on the use of one-dimensional projections. The properties of a depth me…
Sequential Clustering for Functional Data
Ana Justel, Marcela Svarc
This paper presents SeqClusFD, a top-down sequential clustering method for functional data. The clustering algorithm extracts the splitting information either from trajectories, fi…
Feature Selection for Functional Data
Ricardo Fraiman, Yanina Gimenez, Marcela Svarc
In this paper we address the problem of feature selection when the data is functional, we study several statistical procedures including classification, regression and principal co…
Resistant estimates for high dimensional and functional data based on random projections
Ricardo Fraiman, Marcela Svarc
We herein propose a new robust estimation method based on random projections that is adaptive and, automatically produces a robust estimate, while enabling easy computations for hi…
Interpretable Clustering using Unsupervised Binary Trees
Ricardo Fraiman, Badih Ghattas, Marcela Svarc
We herein introduce a new method of interpretable clustering that uses unsupervised binary trees. It is a three-stage procedure, the first stage of which entails a series of recurs…
Clustering using Unsupervised Binary Trees: CUBT
Ricardo Fraiman, Badih Ghattas, Marcela Svarc
We herein introduce a new method of interpretable clustering that uses unsupervised binary trees. It is a three-stage procedure, the first stage of which entails a series of recurs…