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Two Simple but Efficient Algorithms to Recognize Robinson Dissimilarities

Author

Listed:
  • M. Carmona

    (LIS, Aix-Marseille Université, CNRS and Université de Toulon
    École Centrale Marseille)

  • V. Chepoi

    (LIS, Aix-Marseille Université, CNRS and Université de Toulon)

  • G. Naves

    (LIS, Aix-Marseille Université, CNRS and Université de Toulon)

  • P. Préa

    (LIS, Aix-Marseille Université, CNRS and Université de Toulon
    École Centrale Marseille)

Abstract

A dissimilarity d on a set S of size n is said to be Robinson if its matrix can be symmetrically permuted so that its elements do not decrease when moving away from the main diagonal along any row or column. Equivalently, S admits a total order

Suggested Citation

  • M. Carmona & V. Chepoi & G. Naves & P. Préa, 2024. "Two Simple but Efficient Algorithms to Recognize Robinson Dissimilarities," Journal of Classification, Springer;The Classification Society, vol. 41(3), pages 455-479, November.
    • Handle: RePEc:spr:jclass:v:41:y:2024:i:3:d:10.1007_s00357-023-09446-y
    DOI: 10.1007/s00357-023-09446-y
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    References listed on IDEAS

    as
    1. Pascal Préa & Dominique Fortin, 2014. "An Optimal Algorithm To Recognize Robinsonian Dissimilarities," Journal of Classification, Springer;The Classification Society, vol. 31(3), pages 351-385, October.
    2. Victor Chepoi & Bernard Fichet, 1997. "Recognition of Robinsonian dissimilarities," Journal of Classification, Springer;The Classification Society, vol. 14(2), pages 311-325, September.
    3. Laurent, Monique & Seminaroti, M. & Tanigawa, Shin-ichi, 2017. "A structural characterization for certifying robinsonian matrices," Other publications TiSEM 5ecebfb8-804e-4267-8c12-b, Tilburg University, School of Economics and Management.
    4. Fogel, Fajwel & d'Aspremont, Alexandre & Vojnovic, Milan, 2016. "Spectral ranking using seriation," LSE Research Online Documents on Economics 68987, London School of Economics and Political Science, LSE Library.
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