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Journal Articles
- 2024
[j30]Florian Combes
, Ricardo Fraiman, Badih Ghattas:
Subsampling under distributional constraints. Stat. Anal. Data Min. 17(1) (2024)- 2023
- [j29]Ricardo Fraiman, Leonardo Moreno, Thomas Ransford:
A Cramér-Wold theorem for elliptical distributions. J. Multivar. Anal. 196: 105176 (2023) - 2022
- [j28]Alejandro Cholaquidis, Ricardo Fraiman, Leonardo Moreno:
Level set and density estimation on manifolds. J. Multivar. Anal. 189: 104925 (2022) - 2019
- [j27]Ricardo Fraiman, Fabrice Gamboa, Leonardo Moreno:
Connecting pairwise geodesic spheres by depth: DCOPS. J. Multivar. Anal. 169: 81-94 (2019) - [j26]Germán Aneiros, Ricardo Cao, Ricardo Fraiman, Philippe Vieu:
Editorial for the Special Issue on Functional Data Analysis and Related Topics. J. Multivar. Anal. 170: 1-2 (2019) - [j25]Germán Aneiros, Ricardo Cao, Ricardo Fraiman, Christian Genest, Philippe Vieu:
Recent advances in functional data analysis and high-dimensional statistics. J. Multivar. Anal. 170: 3-9 (2019) - [j24]Catherine Aaron, Alejandro Cholaquidis, Ricardo Fraiman, Badih Ghattas:
Multivariate and functional robust fusion methods for structured Big Data. J. Multivar. Anal. 170: 149-161 (2019) - 2017
- [j23]Alejandro Cholaquidis, Antonio Cuevas, Ricardo Fraiman:
On visual distances for spectrum-type functional data. Adv. Data Anal. Classif. 11(1): 5-24 (2017) - [j22]Ricardo Fraiman, Leonardo Moreno, Sebastian Vallejo:
Some hypothesis tests based on random projection. Comput. Stat. 32(3): 1165-1189 (2017) - [j21]Lucía Amoruso, Agustín Ibáñez, Bruno Fonseca, Sebastián Gadea, Lucas Sedeño, Mariano Sigman, Adolfo M. García, Ricardo Fraiman, Daniel Fraiman:
Variability in functional brain networks predicts expertise during action observation. NeuroImage 146: 690-700 (2017) - 2016
- [j20]Ricardo Fraiman, Yanina Gimenez, Marcela Svarc:
Feature selection for functional data. J. Multivar. Anal. 146: 191-208 (2016) - [j19]Alejandro Cholaquidis, Ricardo Fraiman, Juan Kalemkerian, Pamela Llop:
A nonlinear aggregation type classifier. J. Multivar. Anal. 146: 269-281 (2016) - 2014
- [j18]Mathias Bourel, Ricardo Fraiman, Badih Ghattas:
Random average shifted histograms. Comput. Stat. Data Anal. 79: 149-164 (2014) - [j17]Liliana Forzani, Ricardo Fraiman, Pamela Llop:
Corrigendum to "Consistent Nonparametric Regression for Functional Data Under the Stone-Besicovitch Conditions". IEEE Trans. Inf. Theory 60(5): 3069 (2014) - 2013
- [j16]Ricardo Fraiman, Badih Ghattas, Marcela Svarc:
Interpretable clustering using unsupervised binary trees. Adv. Data Anal. Classif. 7(2): 125-145 (2013) - [j15]Ricardo Fraiman, Marcela Svarc:
Resistant estimates for high dimensional and functional data based on random projections. Comput. Stat. Data Anal. 58: 326-338 (2013) - 2012
- [j14]Juan Antonio Cuesta-Albertos, Eustasio del Barrio, Ricardo Fraiman, Carlos Matrán:
Letter to the editor. J. Multivar. Anal. 103(1): 161-162 (2012) - [j13]Ricardo Fraiman, Beatriz Pateiro-López:
Quantiles for finite and infinite dimensional data. J. Multivar. Anal. 108: 1-14 (2012) - [j12]Antonio Cuevas, Ricardo Fraiman:
Corrigendum to "On depth measures and dual statistics. A methodology for dealing with general data" [JMVA 100 (2009) 753-766]. J. Multivar. Anal. 112: 256 (2012) - [j11]Liliana Forzani, Ricardo Fraiman, Pamela Llop:
Consistent Nonparametric Regression for Functional Data Under the Stone-Besicovitch Conditions. IEEE Trans. Inf. Theory 58(11): 6697-6708 (2012) - 2011
- [j10]Pamela Llop, Liliana Forzani, Ricardo Fraiman:
On local times, density estimation and supervised classification from functional data. J. Multivar. Anal. 102(1): 73-86 (2011) - 2010
- [j9]Ricardo Fraiman, Ana Justel, Marcela Svarc:
Pattern recognition via projection-based kNN rules. Comput. Stat. Data Anal. 54(5): 1390-1403 (2010) - 2009
- [j8]Antonio Cuevas, Ricardo Fraiman:
On depth measures and dual statistics. A methodology for dealing with general data. J. Multivar. Anal. 100(4): 753-766 (2009) - [j7]Daniel Carando, Ricardo Fraiman, Pablo Groisman:
Nonparametric likelihood based estimation for a multivariate Lipschitz density. J. Multivar. Anal. 100(5): 981-992 (2009) - [j6]Juan Antonio Cuesta-Albertos, Antonio Cuevas, Ricardo Fraiman:
On projection-based tests for directional and compositional data. Stat. Comput. 19(4): 367-380 (2009) - 2007
- [j5]Juan Antonio Cuesta-Albertos, Eustasio del Barrio, Ricardo Fraiman, Carlos Matrán:
The random projection method in goodness of fit for functional data. Comput. Stat. Data Anal. 51(10): 4814-4831 (2007) - [j4]Juan Antonio Cuesta-Albertos, Ricardo Fraiman:
Impartial trimmed k-means for functional data. Comput. Stat. Data Anal. 51(10): 4864-4877 (2007) - [j3]Antonio Cuevas, Manuel Febrero-Bande, Ricardo Fraiman:
Robust estimation and classification for functional data via projection-based depth notions. Comput. Stat. 22(3): 481-496 (2007) - 2006
- [j2]Antonio Cuevas, Manuel Febrero-Bande, Ricardo Fraiman:
On the use of the bootstrap for estimating functions with functional data. Comput. Stat. Data Anal. 51(2): 1063-1074 (2006) - 2004
- [j1]Antonio Cuevas, Manuel Febrero-Bande, Ricardo Fraiman:
An anova test for functional data. Comput. Stat. Data Anal. 47(1): 111-122 (2004)
Conference and Workshop Papers
- 2003
- [c1]Juan Antonio Cuesta-Albertos, Ricardo Fraiman:
Impartial trimmed means for functional data. Data Depth: Robust Multivariate Analysis, Computational Geometry and Applications 2003: 121-145
Informal and Other Publications
- 2018
- [i1]Alejandro Cholaquidis, Ricardo Fraiman, Mariela Sued:
Semi-supervised learning: When and why it works. CoRR abs/1805.09180 (2018)
Coauthor Index
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