Asymptotics, finite-sample comparisons and applications for two-sample tests with functional data

Qing Jiang; Marie Hušková; Simos G. Meintanis; Lixing ZHU

doi:10.1016/j.jmva.2018.09.002

Asymptotics, finite-sample comparisons and applications for two-sample tests with functional data

Qing Jiang, Marie Hušková, Simos G. Meintanis^*, Lixing ZHU

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

We consider two-sample tests for functional data with observations which may be uni- or multi-dimensional. The new methods are formulated as L₂-type criteria based on empirical characteristic functions and are convenient from the computational point of view. Asymptotic properties are presented. Simulations and two real data applications are conducted in order to evaluate the performance of the proposed tests vis-à-vis other methods.

Original language	English
Pages (from-to)	202-220
Number of pages	19
Journal	Journal of Multivariate Analysis
Volume	170
DOIs	https://doi.org/10.1016/j.jmva.2018.09.002
Publication status	Published - Mar 2019

Scopus Subject Areas

Statistics and Probability
Numerical Analysis
Statistics, Probability and Uncertainty

User-Defined Keywords

Empirical characteristic function
Functional data
Two-sample problem

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10.1016/j.jmva.2018.09.002

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title = "Asymptotics, finite-sample comparisons and applications for two-sample tests with functional data",

abstract = "We consider two-sample tests for functional data with observations which may be uni- or multi-dimensional. The new methods are formulated as L2-type criteria based on empirical characteristic functions and are convenient from the computational point of view. Asymptotic properties are presented. Simulations and two real data applications are conducted in order to evaluate the performance of the proposed tests vis-{\`a}-vis other methods.",

keywords = "Empirical characteristic function, Functional data, Two-sample problem",

author = "Qing Jiang and Marie Hu{\v s}kov{\'a} and Meintanis, {Simos G.} and Lixing ZHU",

note = "Funding Information: The authors are grateful to the Editor-in-Chief, Guest Associate Editor, and referees for comments and suggestions which led to an improved manuscript. M. Hu{\v s}kov{\'a} was partially supported by grant GA{\v C}R , Czech Republic, 15-09663S . S.G. Meintanis was partially supported by grant 11699 of the Special Account for Research Grants (EKE) of the National and Kapodistrian University of Athens . ",

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doi = "10.1016/j.jmva.2018.09.002",

language = "English",

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AU - Jiang, Qing

AU - Hušková, Marie

AU - Meintanis, Simos G.

AU - ZHU, Lixing

N1 - Funding Information: The authors are grateful to the Editor-in-Chief, Guest Associate Editor, and referees for comments and suggestions which led to an improved manuscript. M. Hušková was partially supported by grant GAČR , Czech Republic, 15-09663S . S.G. Meintanis was partially supported by grant 11699 of the Special Account for Research Grants (EKE) of the National and Kapodistrian University of Athens .

PY - 2019/3

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N2 - We consider two-sample tests for functional data with observations which may be uni- or multi-dimensional. The new methods are formulated as L2-type criteria based on empirical characteristic functions and are convenient from the computational point of view. Asymptotic properties are presented. Simulations and two real data applications are conducted in order to evaluate the performance of the proposed tests vis-à-vis other methods.

AB - We consider two-sample tests for functional data with observations which may be uni- or multi-dimensional. The new methods are formulated as L2-type criteria based on empirical characteristic functions and are convenient from the computational point of view. Asymptotic properties are presented. Simulations and two real data applications are conducted in order to evaluate the performance of the proposed tests vis-à-vis other methods.

KW - Empirical characteristic function

KW - Functional data

KW - Two-sample problem

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DO - 10.1016/j.jmva.2018.09.002

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JO - Journal of Multivariate Analysis

JF - Journal of Multivariate Analysis

ER -

Asymptotics, finite-sample comparisons and applications for two-sample tests with functional data

Abstract

Scopus Subject Areas

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