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Tests for separability in nonparametric covariance operators of random surfaces

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Functional Statistics and Related Fields

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

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Abstract

We consider the problem of testing for separability in nonparametric covariance operators of multidimensional functional data is considered. We cast the problem in a tensor product of Hilbert space framework, where the role of the partial trace operator is emphasized, and the tests proposed are computationally tractable. An applications to acoustic phonetic data is also presented.

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Author information

Authors and Affiliations

  1. Statistical Laboratory, Department of Pure Maths and Mathematical Statistics, University of Cambridge, Cambridge, UK

    Shahin Tavakoli, Davide Pigoli & John A. D. Aston

  2. PRDA, Darwin College, Cambridge, UK

    Shahin Tavakoli

Authors
  1. Shahin Tavakoli
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  2. Davide Pigoli
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  3. John A. D. Aston
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Corresponding author

Correspondence to Shahin Tavakoli .

Editor information

Editors and Affiliations

  1. Dept. of Mathematics, University of A Coruña, A Coruña, Spain

    Germán Aneiros

  2. Dept. of Studies in Econ.and Business, University of Eastern Piedmont "Amedeo Avogadro", Novara, Italy

    Enea G. Bongiorno

  3. Dept. of Mathematics, University of A Coruña, A Coruña, Spain

    Ricardo Cao

  4. Toulouse Mathematics Institute (IMT), Paul Sabatier University, Toulouse, France

    Philippe Vieu

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Tavakoli, S., Pigoli, D., Aston, J.A.D. (2017). Tests for separability in nonparametric covariance operators of random surfaces. In: Aneiros, G., G. Bongiorno, E., Cao, R., Vieu, P. (eds) Functional Statistics and Related Fields. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-55846-2_32

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