Tests for equality of several covariance matrix functions for multivariate functional data

IF 1.4 3区 数学 Q2 STATISTICS & PROBABILITY
Zhiping Qiu , Jiangyuan Fan , Jin-Ting Zhang , Jianwei Chen
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引用次数: 0

Abstract

Multivariate functional data are often observed in many scientific fields. This paper considers a multi-sample equal-covariance matrix function testing problem for multivariate functional data. Two new tests are proposed and studied. The asymptotic properties of the two tests under the null hypothesis and a local alternative are investigated. Two methods for approximating the null distributions of the test statistics are described. It is shown that the two tests are root-n consistent. Two simulation studies are conducted to evaluate the finite sample performance of the proposed tests. Finally, the two tests are illustrated via applications to three real multivariate functional data sets.

多元函数数据的几个协方差矩阵函数的相等性检验
在许多科学领域中经常观察到多变量函数数据。本文研究了多元函数数据的多样本等协方差矩阵函数检验问题。提出并研究了两种新的测试方法。研究了在零假设和局部替代条件下这两个检验的渐近性质。介绍了两种近似检验统计量零分布的方法。结果表明,这两个测试是root-n一致的。进行了两次模拟研究,以评估所提出测试的有限样本性能。最后,通过对三个真实的多元函数数据集的应用,说明了这两个检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Multivariate Analysis
Journal of Multivariate Analysis 数学-统计学与概率论
CiteScore
2.40
自引率
25.00%
发文量
108
审稿时长
74 days
期刊介绍: Founded in 1971, the Journal of Multivariate Analysis (JMVA) is the central venue for the publication of new, relevant methodology and particularly innovative applications pertaining to the analysis and interpretation of multidimensional data. The journal welcomes contributions to all aspects of multivariate data analysis and modeling, including cluster analysis, discriminant analysis, factor analysis, and multidimensional continuous or discrete distribution theory. Topics of current interest include, but are not limited to, inferential aspects of Copula modeling Functional data analysis Graphical modeling High-dimensional data analysis Image analysis Multivariate extreme-value theory Sparse modeling Spatial statistics.
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