Generalized additive models for functional data

The aim of this paper is to extend the ideas of generalized additive models for multivariate data (with known or unknown link function) to functional data covariates. The proposed algorithm is a modified version of the local scoring and backfitting algorithms that allows for the nonparametric estimation of the link function. This algorithm would be applied to predict a binary response example. Copyright Sociedad de Estadística e Investigación Operativa 2013

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Year of publication:	2013
Authors:	Febrero-Bande, Manuel ; González-Manteiga, Wenceslao
Published in:	TEST: An Official Journal of the Spanish Society of Statistics and Operations Research. - Springer. - Vol. 22.2013, 2, p. 278-292
Publisher:	Springer
Subject:	Functional data \| Generalized additive models \| Generalized linear models

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010994269