Generalized additive models for functional data
Generalized additive models for functional data
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DOI：
10.1007/s11749-012-0308-0
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发表时间：
2013-06-01
期刊：
影响因子：
1.3
通讯作者：
Gonzalez-Manteiga, Wenceslao
中科院分区：
文献类型：
--
作者：
Febrero-Bande, Manuel;Gonzalez-Manteiga, Wenceslao
本文的目的是将多元数据（具有已知或未知链接函数）的广义加性模型的思想推广到函数数据协变量。提出的算法是局部评分和反向拟合算法的改进版本，允许链路函数的非参数估计。该算法将用于预测一个二元响应示例。
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.