| Loss of the mitochondrial bioenergetic capacity underlies the glucose avidity of carcinomas F López-Ríos, M Sánchez-Aragó, E García-García, ÁD Ortega, ... Cancer research 67 (19), 9013-9017, 2007 | 241 | 2007 |
| Principal components for multivariate functional data JR Berrendero, A Justel, M Svarc Computational Statistics & Data Analysis 55 (9), 2619-2634, 2011 | 193 | 2011 |
| Time series clustering based on forecast densities AM Alonso, JR Berrendero, A Hernández, A Justel Computational Statistics & Data Analysis 51 (2), 762-776, 2006 | 117 | 2006 |
| The mRMR variable selection method: a comparative study for functional data JR Berrendero, A Cuevas, JL Torrecilla Journal of Statistical Computation and Simulation 86 (5), 891-907, 2016 | 73 | 2016 |
| Variable selection in functional data classification: a maxima-hunting proposal JR Berrendero, A Cuevas, JL Torrecilla Statistica Sinica 26, 619-638, 2016 | 69 | 2016 |
| On the use of reproducing kernel Hilbert spaces in functional classification JR Berrendero, A Cuevas, JL Torrecilla Journal of the American Statistical Association, 2017 | 68 | 2017 |
| On Mahalanobis distance in functional settings JR Berrendero, B Bueno-Larraz, A Cuevas Journal of Machine Learning Research 21 (9), 1-33, 2020 | 49 | 2020 |
| Maximum bias curves for robust regression with non-elliptical regressors JR Berrendero, RH Zamar Annals of statistics, 224-251, 2001 | 35 | 2001 |
| Reverse phase protein microarrays quantify and validate the bioenergetic signature as biomarker in colorectal cancer M Aldea, J Clofent, CN De Arenas, M Chamorro, M Velasco, ... Cancer letters 311 (2), 210-218, 2011 | 34 | 2011 |
| Testing multivariate uniformity: The distance‐to‐boundary method JR Berrendero, A Cuevas, F Vjosázquez‐grande Canadian Journal of Statistics 34 (4), 693-707, 2006 | 34 | 2006 |
| An RKHS model for variable selection in functional linear regression JR Berrendero, B Bueno-Larraz, A Cuevas Journal of Multivariate Analysis 170, 25-45, 2019 | 30* | 2019 |
| A multivariate uniformity test for the case of unknown support JR Berrendero, A Cuevas, B Pateiro-López Statistics and Computing 22 (1), 259-271, 2012 | 26 | 2012 |
| On the maximum bias functions of MM-estimates and constrained M-estimates of regression JR Berrendero, BVM Mendes, DE Tyler Annals of Statistics 35 (1), 13-40, 2007 | 25 | 2007 |
| Tests for the Second Order Stochastic Dominance Based on L-Statistics JR Berrendero, J Cárcamo Journal of Business & Economic Statistics 29 (2), 260-270, 2011 | 24 | 2011 |
| High-fat diet induces metabolic changes and reduces oxidative stress in female mouse hearts I Barba, E Miró-Casas, JL Torrecilla, E Pladevall, S Tejedor, ... The Journal of Nutritional Biochemistry 40, 187-193, 2017 | 21 | 2017 |
| Shape classification based on interpoint distance distributions JR Berrendero, A Cuevas, B Pateiro-López Journal of Multivariate Analysis 146, 237-247, 2016 | 19 | 2016 |
| A geometrically motivated parametric model in manifold estimation JR Berrendero, A Cholaquidis, A Cuevas, R Fraiman Statistics 48 (5), 983-1004, 2014 | 15 | 2014 |
| On functional logistic regression: some conceptual issues JR Berrendero, B Bueno-Larraz, A Cuevas Test 32 (1), 321-349, 2023 | 13* | 2023 |
| Characterizations of exponentiality within the HNBUE class and related tests JR Berrendero, J Cárcamo Journal of Statistical Planning and Inference 139 (7), 2399-2406, 2009 | 12 | 2009 |
| Facing network management challenges with functional data analysis: Techniques & opportunities D Muelas, JE Lopez de Vergara, JR Berrendero, J Ramos, J Aracil Mobile Networks and Applications 22 (6), 1124-1136, 2017 | 10 | 2017 |
