| An anova test for functional data A Cuevas, M Febrero, R Fraiman Computational statistics & data analysis 47 (1), 111-122, 2004 | 503 | 2004 |
| Statistical computing in functional data analysis: The R package fda. usc M Febrero-Bande, MO de la Fuente Journal of statistical Software 51, 1-28, 2012 | 434 | 2012 |
| Robust estimation and classification for functional data via projection-based depth notions A Cuevas, M Febrero, R Fraiman Computational Statistics 22 (3), 481-496, 2007 | 363 | 2007 |
| Outlier detection in functional data by depth measures, with application to identify abnormal NOx levels M Febrero, P Galeano, W González‐Manteiga Environmetrics: The official journal of the International Environmetrics …, 2008 | 289 | 2008 |
| On the use of the bootstrap for estimating functions with functional data A Cuevas, M Febrero, R Fraiman Computational statistics & data analysis 51 (2), 1063-1074, 2006 | 230 | 2006 |
| Linear functional regression: the case of fixed design and functional response A Cuevas, M Febrero, R Fraiman Canadian Journal of Statistics 30 (2), 285-300, 2002 | 216 | 2002 |
| An extensive experimental survey of regression methods M Fernández-Delgado, MS Sirsat, E Cernadas, S Alawadi, S Barro, ... Neural Networks 111, 11-34, 2019 | 167 | 2019 |
| Cluster analysis: a further approach based on density estimation A Cuevas, M Febrero, R Fraiman Computational statistics & data analysis 36 (4), 441-459, 2001 | 149 | 2001 |
| Modelling of the monthly and daily behaviour of the runoff of the Xallas river using Box–Jenkins and neural networks methods M Castellano-Méndez, W González-Manteiga, M Febrero-Bande, ... Journal of hydrology 296 (1-4), 38-58, 2004 | 144 | 2004 |
| Estimating the number of clusters A Cuevas, M Febrero, R Fraiman Canadian Journal of Statistics 28 (2), 367-382, 2000 | 144 | 2000 |
| A simple multiway ANOVA for functional data JA Cuesta-Albertos, M Febrero-Bande Test 19 (3), 537-557, 2010 | 131 | 2010 |
| A functional analysis of NOx levels: location and scale estimation and outlier detection M Febrero, P Galeano, W González-Manteiga Computational Statistics 22 (3), 411-427, 2007 | 116 | 2007 |
| Functional principal component regression and functional partial least‐squares regression: An overview and a comparative study M Febrero‐Bande, P Galeano, W González‐Manteiga International Statistical Review 85 (1), 61-83, 2017 | 83 | 2017 |
| Generalized additive models for functional data M Febrero-Bande, W González-Manteiga Test 22, 278-292, 2013 | 72 | 2013 |
| A goodness-of-fit test for the functional linear model with scalar response E García-Portugués, W González-Manteiga, M Febrero-Bande Journal of Computational and Graphical Statistics 23 (3), 761-778, 2014 | 62 | 2014 |
| Flexible spatio-temporal stationary variogram models R Fernández-Casal, W González-Manteiga, M Febrero-Bande Statistics and Computing 13, 127-136, 2003 | 55 | 2003 |
| Nonparametric kernel estimation of an isotropic variogram PH Garcı́a-Soidán, M Febrero-Bande, W González-Manteiga Journal of Statistical Planning and Inference 121 (1), 65-92, 2004 | 52 | 2004 |
| Predicting using box—jenkins, nonparametric, and bootstrap techniques I García-Jurado, W González-Manteiga, JM Prada-Sánchez, ... Technometrics 37 (3), 303-310, 1995 | 50 | 1995 |
| Flexible regression models for estimating postmortem interval (PMI) in forensic medicine JI Munoz Barus, M Febrero‐Bande, C Cadarso‐Suárez Statistics in medicine 27 (24), 5026-5038, 2008 | 46 | 2008 |
| A reliable method for estimating the postmortem interval from the biochemistry of the vitreous humor, temperature and body weight C Cordeiro, L Ordóñez-Mayán, E Lendoiro, M Febrero-Bande, DN Vieira, ... Forensic science international 295, 157-168, 2019 | 45 | 2019 |
Wenceslao Gonzalez ManteigaCatedrático de Universidad, Universidad de Santiago de CompostelaVerified email at usc.es
