Please use this identifier to cite or link to this item: https://doi.org/10.1080/03610920902755839
Title: Two samples tests for functional data
Authors: Zhang, C.
Peng, H.
Zhang, J.-T. 
Keywords: Bootstrap-based test statistic
Functional data
Hypothesis test
L2-norm-based test statistic
Issue Date: Jan-2010
Source: Zhang, C., Peng, H., Zhang, J.-T. (2010-01). Two samples tests for functional data. Communications in Statistics - Theory and Methods 39 (4) : 559-578. ScholarBank@NUS Repository. https://doi.org/10.1080/03610920902755839
Abstract: Data in many experiments arises as curves and therefore it is natural to use a curve as a basic unit in the analysis, which is in terms of functional data analysis (FDA). Functional curves are encountered when units are observed over time. Although the whole function curve itself is not observed, a sufficiently large number of evaluations, as is common with modern recording equipment, is assumed to be available. In this article, we consider the statistical inference for the mean functions in the two samples problem drawn from functional data sets, in which we assume that functional curves are observed, that is, we consider the test if these two groups of curves have the same mean functional curve when the two groups of curves without noise are observed. The L2-norm based and bootstrap-based test statistics are proposed. It is shown that the proposed methodology is flexible. Simulation study and real-data examples are used to illustrate our techniques.
Source Title: Communications in Statistics - Theory and Methods
URI: http://scholarbank.nus.edu.sg/handle/10635/105445
ISSN: 03610926
DOI: 10.1080/03610920902755839
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