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The K-INDSCAL Model for Heterogeneous Three-Way Dissimilarity Data

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  • Laura Bocci
  • Maurizio Vichi

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  • Laura Bocci & Maurizio Vichi, 2011. "The K-INDSCAL Model for Heterogeneous Three-Way Dissimilarity Data," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 691-714, October.
  • Handle: RePEc:spr:psycho:v:76:y:2011:i:4:p:691-714
    DOI: 10.1007/s11336-011-9225-5
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    References listed on IDEAS

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    1. J. Carroll & Jih-Jie Chang, 1970. "Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition," Psychometrika, Springer;The Psychometric Society, vol. 35(3), pages 283-319, September.
    2. Jos Berge & Henk Kiers, 1991. "Some clarifications of the CANDECOMP algorithm applied to INDSCAL," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 317-326, June.
    3. Michel Wedel & Wayne DeSarbo, 1998. "Mixtures of (constrained) ultrametric trees," Psychometrika, Springer;The Psychometric Society, vol. 63(4), pages 419-443, December.
    4. Jos Berge & Henk Kiers & Wim Krijnen, 1993. "Computational solutions for the problem of negative saliences and nonsymmetry in INDSCAL," Journal of Classification, Springer;The Classification Society, vol. 10(1), pages 115-124, January.
    5. Suzanne Winsberg & Geert Soete, 1993. "A latent class approach to fitting the weighted Euclidean model, clascal," Psychometrika, Springer;The Psychometric Society, vol. 58(2), pages 315-330, June.
    6. Lawrence Hubert & Phipps Arabie, 1985. "Comparing partitions," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 193-218, December.
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    Citations

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    Cited by:

    1. Laura Bocci & Donatella Vicari, 2017. "GINDCLUS: Generalized INDCLUS with External Information," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 355-381, June.
    2. Dawn Iacobucci & Doug Grisaffe & Wayne DeSarbo, 2017. "Statistical perceptual maps: using confidence region ellipses to enhance the interpretations of brand positions in multidimensional scaling," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(3), pages 81-98, December.

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