文章基本信息

标题：Robust Regression for Functional Time Series Data
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作者：Mohammed Kadi Attouch ; Ali Laksaci ; Elias Ould Saïd 等
期刊名称：JOURNAL OF THE JAPAN STATISTICAL SOCIETY
印刷版ISSN：1882-2754
电子版ISSN：1348-6365
出版年度：2012
卷号：42
期号：2
页码：125-143
DOI：10.14490/jjss.42.125
出版社：JAPAN STATISTICAL SOCIETY
摘要：We propose a family of robust nonparametric estimators for regression function based on the kernel method. We establish the almost complete convergence rate of these estimators under the α-mixing assumption and on the concentration properties on small balls of the probability measure of the functional regressors. Some applications to physics real data have been made. These results are extensions to dependent data of the results given by Azzedine et al. (2008).
关键词：Almost sure convergence;functional data;kernel;estimate;nonparametric model;robust estimation;small balls probability;strong mixing