On the use of the bootstrap for estimating functions with functional data
On the use of the bootstrap for estimating functions with functional data
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DOI：
10.1016/j.csda.2005.10.012
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发表时间：
2006-11-15
影响因子：
1.8
通讯作者：
Fraiman, Ricardo
中科院分区：
文献类型：
--
作者：
Cuevas, Antonio;Febrero, Manuel;Fraiman, Ricardo
考虑了函数数据和函数估计目标的自举方法。用蒙特卡罗方法分析了几种函数估计器的自举置信带（用不同的重采样方法得到）的性能。其中一些估计器（例如，修剪的函数平均值）依赖于对函数数据的深度概念的使用，并且在文献中还没有得到太多的关注。并对心脏病学研究中的一个实际数据实例进行了分析。在更理论化的方面，简要讨论了当涉及函数数据和函数参数时，对自举方法的渐近有效性提供了一些见解。(c) 2005 Elsevier B.V.版权所有
The bootstrap methodology for functional data and functional estimation target is considered. A Monte Carlo study analyzing the performance of the bootstrap confidence bands (obtained with different resampling methods) of several functional estimators is presented. Some of these estimators (e.g., the trimmed functional mean) rely on the use of depth notions for functional data and do not have received yet much attention in the literature. A real data example in cardiology research is also analyzed. In a more theoretical aspect, a brief discussion is given providing some insights on the asymptotic validity of the bootstrap methodology when functional data, as well as a functional parameter, are involved. (c) 2005 Elsevier B.V. All rights reserved.