Statistical inference for stochastic processes: Two-sample hypothesis tests

被引：10

作者：

Ghiglietti, Andrea ^{[1
]}

Ieva, Francesca ^{[1
]}

Paganoni, Anna Maria ^{[2
]}

机构：

[1] Univ Milan, Dept Math F Enriques, I-20122 Milan, Italy

[2] Politecn Milan, MOX Modeling & Sci Comp, Milan, Italy

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2017年 / 180卷

关键词：

Functional data; Distances in L-2; Hypothesis tests; Two-sample problems; FUNCTIONAL DATA-ANALYSIS;

D O I：

10.1016/j.jspi.2016.08.004

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：

In this paper, we present inferential procedures to compare the means of two samples of functional data. The proposed tests are based on a suitable generalization of Mahalanobis distance to the Hilbert space of square integrable functions defined on a compact interval. The only conditions required concern the moments and the independence of the functional data, while the distribution of the processes generating the data is not needed to be specified. Test procedures are proposed for both the cases of known and unknown variance-covariance structures, and asymptotic properties of test statistics are deeply studied. A simulation study and a real case data analysis are also presented. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：49 / 68

页数：20

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