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Testing for lack of dependence between functional variables
被引:3
|作者:
Jiofack, Jean Gerard Aghoukeng
[1
,2
]
Nkiet, Guy Martial
[1
]
机构:
[1] Univ Sci & Tech Masuku, Unite Rech Math & Informat, Franceville, Gabon
[2] Univ Yaounde I, Fac Sci, Dept Math, Yaounde, Cameroon
关键词:
Lack of dependence;
Test;
Functional variables;
D O I:
10.1016/j.spl.2010.03.018
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 introduce a test for the lack of dependence between two random variables valued into real Hilbert spaces. Here, we consider lack of dependence in the broader sense, that is, non-correlation. The test statistic is similar to the one proposed by Kokoszka et al. (2008) for testing for no effect in the linear functional model. The asymptotic distribution under the null hypothesis of this statistic is obtained as well as a consistency result for the proposed test. Applications to the case of functional variables are indicated and simulations show, in this context, the performance of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.
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页码:1210 / 1217
页数:8
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