An anova test for functional data
An anova test for functional data
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DOI：
10.1016/j.csda.2003.10.021
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发表时间：
2004-08-01
影响因子：
1.8
通讯作者：
Fraiman, R
中科院分区：
文献类型：
--
作者：
Cuevas, A;Febrero, M;Fraiman, R
给定k个独立样本的功能数据的检验问题的零假设的平等，其各自的平均功能被认为是。因此，该设置与经典的单因素方差分析模型非常相似，但所研究的k个样本由函数数据组成。提出了一个简单的自然测试这个问题。它可以被看作是著名的方差F检验的渐近版本。证明了该方法的渐近有效性。本文提出了一种数值蒙特卡罗方法来处理检验统计量的渐近分布。包括模拟研究和实验心脏病学的一个真实数据的例子被认为是在一些细节。(C)2003 Elsevier B.V.保留所有权利。
Given k independent samples of functional data the problem of testing the null hypothesis of equality of their respective mean functions is considered. So the setting is quite similar to that of the classical one-way anova model but the k samples under study consist of functional data. A simple natural test for this problem is proposed. It can be seen as an asymptotic version of the well-known anova F-test. The asymptotic validity of the method is shown. A numerical Monte Carlo procedure is proposed to handle in practice the asymptotic distribution of the test statistic. A simulation study is included and a real-data example in experimental cardiology is considered in some detail. (C) 2003 Elsevier B.V. All rights reserved.