6533b86ffe1ef96bd12cd279

RESEARCH PRODUCT

Varying-coefficient functional linear regression models

Hervé CardotPascal Sarda

subject

Statistics and ProbabilityPolynomial regressionStatistics::TheoryProper linear modelMultivariate adaptive regression splines010504 meteorology & atmospheric sciencesLocal regression01 natural sciences62G05 (62G20 62M20)Statistics::ComputationNonparametric regressionStatistics::Machine Learning010104 statistics & probabilityLinear regressionStatisticsStatistics::Methodology0101 mathematicsSegmented regressionRegression diagnosticComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesMathematics

description

This article considers a generalization of the functional linear regression in which an additional real variable influences smoothly the functional coefficient. We thus define a varying-coefficient regression model for functional data. We propose two estimators based, respectively, on conditional functional principal regression and on local penalized regression splines and prove their pointwise consistency. We check, with the prediction one day ahead of ozone concentration in the city of Toulouse, the ability of such nonlinear functional approaches to produce competitive estimations.

10.1080/03610920802105176https://hal.archives-ouvertes.fr/hal-00634971