M. Febrero–Bande

Statistics and Probability · 2004–2020

A researcher in the Science corpus: 8 papers; trusts 81 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 130 citations into it; #1,878 of 12,932 by trust here, #2,629 by citations
• Artificial Intelligence — 56 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Statistical Learning Theory — 16 citations into it
• Control and Systems Engineering — 13 citations into it
• Analytical Chemistry — 11 citations into it
• Computational Mechanics — 11 citations into it
• Management Science and Operations Research — 8 citations into it

Whom M. Febrero–Bande trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Gareth M. James
2. Peter Hall
3. Frédéric Ferraty
4. Hervé Cardot
5. Trevor J. Hastie
6. Robert Tibshirani
7. H. Muller
8. Nicolai Meinshausen
9. Nicole Krämer
10. Jerome H. Friedman

Who trusts M. Febrero–Bande overall

1. Dominik Liebl
2. Wenceslao González-Manteiga
3. Laura Freijeiro-González
4. Pedro Galeano
5. Karl Mosler
6. Daniel Gervini
7. Tomasz Górecki
8. Gerda Claeskens
9. Ana-Maria Staicu
10. Jin-Ting Zhang

Papers from M. Febrero–Bande's perspective

Ordered by how strongly the researchers M. Febrero–Bande trusts endorse each paper. Same corpus, a different order for every researcher.

1. Regression Shrinkage and Selection via the Lasso
2. Model selection and estimation in regression with grouped variables
3. High-dimensional graphs and variable selection with the Lasso
4. The Adaptive Lasso and Its Oracle Properties
5. [A Statistical View of Some Chemometrics Regression Tools]: Discussion
6. On Model Selection Consistency of Lasso
7. © Institute of Mathematical Statistics, 2004 LEAST ANGLE REGRESSION
8. SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR
9. Estimating the Dimension of a Model
10. Bagging Predictors

Their papers

• An anova test for functional data (2004) — 497 citations
• Robust estimation and classification for functional data via projection-based depth notions (2007) — 328 citations
• Statistical Computing in Functional Data Analysis: The R Package fda.usc (2012) — 442 citations
• Generalized additive models for functional data (2013) — 63 citations
• A Goodness-of-Fit Test for the Functional Linear Model with Scalar Response (2012) — 74 citations
• A Critical Review of LASSO and Its Derivatives for Variable Selection Under Dependence Among Covariates (2020) — 129 citations
• An extensive experimental survey of regression methods (2019) — 317 citations
• Functional Principal Component Regression and Functional Partial Least‐squares Regression: An Overview and a Comparative Study (2017) — 101 citations