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Kernel based method for the k-sample problem with functional data

Author

Listed:
  • Armando S. K. Balogoun
  • Guy M. Nkiet
  • Carlos Ogouyandjou

Abstract

In this paper, we deal with the problem of testing for the equality of k probability distributions defined on (X,B), where X is a metric space and B is the corresponding Borel σ-field. We introduce a test statistic based on reproducing kernel Hilbert space embeddings and derive its asymptotic distribution under the null hypothesis. Simulations show that the introduced procedure outperforms a known method.

Suggested Citation

  • Armando S. K. Balogoun & Guy M. Nkiet & Carlos Ogouyandjou, 2022. "Kernel based method for the k-sample problem with functional data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(17), pages 5826-5849, September.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:17:p:5826-5849
    DOI: 10.1080/03610926.2020.1849719
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