Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Two Sample Test for Functional Data

  • Lee, Jong Soo (Department of Mathematical Sciences, University of Massachusetts Lowell) ;
  • Cox, Dennis D. (Department of Statistics, Rice University) ;
  • Follen, Michele (Department of Obstetrics and Gynecology, Brookdale University Hospital and Medical Center)
  • Received : 2014.11.24
  • Accepted : 2015.01.31
  • Published : 2015.03.31
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Abstract

We consider testing equality of mean functions from two samples of functional data. A novel test based on the adaptive Neyman methodology applied to the Hotelling's T-squared statistic is proposed. Under the enlarged null hypothesis that the distributions of the two populations are the same, randomization methods are proposed to find a null distribution which gives accurate significance levels. An extensive simulation study is presented which shows that the proposed test works very well in comparison with several other methods under a variety of alternatives and is one of the best methods for all alternatives, whereas the other methods all show weak power at some alternatives. An application to a real-world data set demonstrates the applicability of the method.

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References

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