| Robust principal component analysis for functional data N Locantore, JS Marron, DG Simpson, N Tripoli, JT Zhang, KL Cohen, ... Test 8, 1-73, 1999 | 468 | 1999 |
| Using principal components for estimating logistic regression with high-dimensional multicollinear data AM Aguilera, M Escabias, MJ Valderrama Computational Statistics & Data Analysis 50 (8), 1905-1924, 2006 | 291 | 2006 |
| Principal component estimation of functional logistic regression: discussion of two different approaches M Escabias, AM Aguilera, MJ Valderrama Journal of Nonparametric Statistics 16 (3-4), 365-384, 2004 | 198 | 2004 |
| Modeling environmental data by functional principal component logistic regression M Escabias, AM Aguilera, MJ Valderrama Environmetrics: The official journal of the International Environmetrics …, 2005 | 125 | 2005 |
| Functional PLS logit regression model M Escabias, AM Aguilera, MJ Valderrama Computational Statistics & Data Analysis 51 (10), 4891-4902, 2007 | 105 | 2007 |
| Using basis expansions for estimating functional PLS regression: applications with chemometric data AM Aguilera, M Escabias, C Preda, G Saporta Chemometrics and Intelligent Laboratory Systems 104 (2), 289-305, 2010 | 90 | 2010 |
| Analysis of the statistics of device-to-device and cycle-to-cycle variability in TiN/Ti/Al: HfO2/TiN RRAMs E Pérez, D Maldonado, C Acal, JE Ruiz-Castro, FJ Alonso, AM Aguilera, ... Microelectronic Engineering 214, 104-109, 2019 | 87 | 2019 |
| Functional principal components analysis by choice of norm FA Ocaña, AM Aguilera, MJ Valderrama Journal of multivariate analysis 71 (2), 262-276, 1999 | 85 | 1999 |
| New modeling approaches based on varimax rotation of functional principal components C Acal, AM Aguilera, M Escabias Mathematics 8 (11), 2085, 2020 | 80 | 2020 |
| Comparative study of different B-spline approaches for functional data AM Aguilera, MC Aguilera-Morillo Mathematical and Computer Modelling 58 (7-8), 1568-1579, 2013 | 73 | 2013 |
| Computational considerations in functional principal component analysis FA Ocaña, AM Aguilera, M Escabias Computational Statistics 22 (3), 449-465, 2007 | 68 | 2007 |
| Time series statistical analysis: A powerful tool to evaluate the variability of resistive switching memories JB Roldán, FJ Alonso, AM Aguilera, D Maldonado, M Lanza Journal of Applied Physics 125 (17), 2019 | 66 | 2019 |
| Modelling the mean of a doubly stochastic Poisson process by functional data analysis PR Bouzas, MJ Valderrama, AM Aguilera, N Ruiz-Fuentes Computational Statistics & Data Analysis 50 (10), 2655-2667, 2006 | 62 | 2006 |
| Penalized PCA approaches for B-spline expansions of smooth functional data AM Aguilera, MC Aguilera-Morillo Applied Mathematics and Computation 219 (14), 7805-7819, 2013 | 61 | 2013 |
| An approximated principal component prediction model for continuous‐time stochastic processes AM Aguilera, FA Ocaña, MJ Valderrama Applied Stochastic Models and Data Analysis 13 (2), 61-72, 1997 | 61 | 1997 |
| Tablas de contingencia bidimensionales AM Aguilera del Pino España: La muralla, 2001 | 55 | 2001 |
| Forecasting time series by functional PCA. Discussion of several weighted approaches AM Aguilera, FA Ocaña, MJ Valderrama Computational Statistics 14, 443-467, 1999 | 55 | 1999 |
| Memristor variability and stochastic physical properties modeling from a multivariate time series approach FJ Alonso, D Maldonado, AM Aguilera, JB Roldán Chaos, Solitons & Fractals 143, 110461, 2021 | 53 | 2021 |
| Penalized spline approaches for functional logit regression MC Aguilera-Morillo, AM Aguilera, M Escabias, MJ Valderrama Test 22, 251-277, 2013 | 51 | 2013 |
| Approximation of estimators in the PCA of a stochastic process using B-splines AM Aguilera, R Gutiérrez, MJ Valderrama Communications in Statistics-Simulation and Computation 25 (3), 671-690, 1996 | 51 | 1996 |