Presmoothing in functional linear regression

被引：2
|
作者：
Martinez-Calvo, Adela [1 ]
机构：
[1] Univ Santiago de Compostela, Santiago De Compostela, Spain
来源：
FUNCTIONAL AND OPERATORIAL STATISTICS | 2008年
关键词：
D O I：
10.1007/978-3-7908-2062-1_34
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We consider the functional linear model with scalar response Y and explanatory variable X valued in a functional space. Functional Principal Components Analysis (FPCA) have been used to estimate the model parameter in recent literature. We propose to modify this methodology by presmoothing either X or Y. For these new estimates, consistency is stated and their efficiency by comparison with the FPCA approach are studied.
引用
收藏
页码：223 / 229
页数：7
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