most citedVariable selection in functional regression models: a review

40 citations · 98 across the 9 of their papers we have counts for

collaborators

9 papers

stat.ME2026

kNN estimation in semi-functional partial linear regression with missing responses at random

Germán Aneiros, Silvia Novo

This paper considers a partial linear regression model with scalar response missing at random, one finite-dimensional covariate (a vector, ) and one infinite-dimensional covaria…

stat.ME2024

fsemipar: an R package for SoF semiparametric regression

Silvia Novo, Germán Aneiros

Functional data analysis has become a tool of interest in applied areas such as economics, medicine, and chemistry. Among the techniques developed in recent literature, functional…

stat.ME2024★ 1 cited

Semi-functional partial linear regression with measurement error: An approach based on NN estimation

Silvia Novo, Germán Aneiros, Philippe Vieu

This paper focuses on a semiparametric regression model in which the response variable is explained by the sum of two components. One of them is parametric (linear), the correspond…

stat.ME2024★ 40 cited

Variable selection in functional regression models: a review

Germán Aneiros, Silvia Novo, Philippe Vieu

Despite of various similar features, Functional Data Analysis and High-Dimensional Data Analysis are two major fields in Statistics that grew up recently almost independently one f…

stat.ME2024★ 2 cited

Fast and efficient algorithms for sparse semiparametric bi-functional regression

Silvia Novo, Philippe Vieu, Germán Aneiros

A new sparse semiparametric model is proposed, which incorporates the influence of two functional random variables in a scalar response in a flexible and interpretable manner. One…

stat.ME2024★ 7 cited

A NN procedure in semiparametric functional data analysis

Silvia Novo, Germán Aneiros, Philippe Vieu

A fast and flexible NN procedure is developed for dealing with a semiparametric functional regression model involving both partial-linear and single-index components. Rates of u…

math.ST2024★ 13 cited

Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables

Silvia Novo, Germán Aneiros, Philippe Vieu

This paper aims to front with dimensionality reduction in regression setting when the predictors are a mixture of functional variable and high-dimensional vector. A flexible model,…

math.ST2024★ 33 cited

Automatic and location-adaptive estimation in functional single-index regression

Silvia Novo, Germán Aneiros, Philippe Vieu

This paper develops a new automatic and location-adaptive procedure for estimating regression in a Functional Single-Index Model (FSIM). This procedure is based on -Nearest Neig…

stat.ME2024★ 2 cited

Bootstrap prediction regions for daily curves of electricity demand and price using functional data

Rebeca Peláez, Germán Aneiros, Juan Vilar

The aim of this paper is to compute one-day-ahead prediction regions for daily curves of electricity demand and price. Three model-based procedures to construct general prediction…