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CO-tucker: a new method for the simultaneous analysis of a sequence of paired tables

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  • Susana Mendes
  • M. José Fernández-Gómez
  • Sónia Cotrim Marques
  • Miguel Ângelo Pardal
  • Ulisses Miranda Azeiteiro
  • M. Purificación Galindo-Villardón

Abstract

Relationships between species and their environment are a key component to understand ecological communities. Usually, this kind of data are repeated over time or space for communities and their environment, which leads to a sequence of pairs of ecological tables, i.e. multi-way matrices. This work proposes a new method which is a combined approach of STATICO and Tucker3 techniques and deals to the problem of describing not only the stable part of the dynamics of structure–function relationships between communities and their environment (in different locations and/or at different times), but also the interactions and changes associated with the ecosystems’ dynamics. At the same time, emphasis is given to the comparison with the STATICO method on the same (real) data set, where advantages and drawbacks are explored and discussed. Thus, this study produces a general methodological framework and develops a new technique to facilitate the use of these practices by researchers. Furthermore, from this first approach with estuarine environmental data one of the major advantages of modeling ecological data sets with the CO-TUCKER model is the gain in interpretability.

Suggested Citation

  • Susana Mendes & M. José Fernández-Gómez & Sónia Cotrim Marques & Miguel Ângelo Pardal & Ulisses Miranda Azeiteiro & M. Purificación Galindo-Villardón, 2017. "CO-tucker: a new method for the simultaneous analysis of a sequence of paired tables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(15), pages 2729-2755, November.
    • Handle: RePEc:taf:japsta:v:44:y:2017:i:15:p:2729-2755
    DOI: 10.1080/02664763.2016.1261815
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    References listed on IDEAS

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    1. Harold Hotelling, 1936. "Simplified calculation of principal components," Psychometrika, Springer;The Psychometric Society, vol. 1(1), pages 27-35, March.
    2. Ledyard Tucker, 1966. "Some mathematical notes on three-mode factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 31(3), pages 279-311, September.
    3. Harshman, Richard A. & Lundy, Margaret E., 1994. "PARAFAC: Parallel factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 18(1), pages 39-72, August.
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    Cited by:

    1. Mariela González-Narváez & María José Fernández-Gómez & Susana Mendes & José-Luis Molina & Omar Ruiz-Barzola & Purificación Galindo-Villardón, 2021. "Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO," Sustainability, MDPI, vol. 13(11), pages 1-25, May.

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