IDEAS home Printed from https://ideas.repec.org/a/spr/jclass/v14y1997i2p195-224.html
   My bibliography  Save this article

Asymmetric multidimensional scaling of two-mode three-way proximities

Author

Listed:
  • Akinori Okada
  • Tadashi Imaizumi

Abstract

No abstract is available for this item.

Suggested Citation

  • Akinori Okada & Tadashi Imaizumi, 1997. "Asymmetric multidimensional scaling of two-mode three-way proximities," Journal of Classification, Springer;The Classification Society, vol. 14(2), pages 195-224, September.
    • Handle: RePEc:spr:jclass:v:14:y:1997:i:2:p:195-224
    DOI: 10.1007/s003579900010
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s003579900010
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s003579900010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.
    2. 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.
    3. Berrie Zielman & Willem Heiser, 1993. "Analysis of asymmetry by a slide-vector," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 101-114, March.
    4. Richard A. Harshman & Paul E. Green & Yoram Wind & Margaret E. Lundy, 1982. "A Model for the Analysis of Asymmetric Data in Marketing Research," Marketing Science, INFORMS, vol. 1(2), pages 205-242.
    5. David Weeks & P. Bentler, 1982. "Restricted multidimensional scaling models for asymmetric proximities," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 201-208, June.
    6. Wayne S. Desarbo & Ajay K. Manrai, 1992. "A New Multidimensional Scaling Methodology for the Analysis of Asymmetric Proximity Data in Marketing Research," Marketing Science, INFORMS, vol. 11(1), pages 1-20.
    7. J. Kruskal, 1964. "Nonmetric multidimensional scaling: A numerical method," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 115-129, June.
    8. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    9. Louis Guttman, 1968. "A general nonmetric technique for finding the smallest coordinate space for a configuration of points," Psychometrika, Springer;The Psychometric Society, vol. 33(4), pages 469-506, December.
    10. C. Horan, 1969. "Multidimensional scaling: Combining observations when individuals have different perceptual structures," Psychometrika, Springer;The Psychometric Society, vol. 34(2), pages 139-165, June.
    11. Warren Torgerson, 1952. "Multidimensional scaling: I. Theory and method," Psychometrika, Springer;The Psychometric Society, vol. 17(4), pages 401-419, December.
    12. Peter Schönemann, 1972. "An algebraic solution for a class of subjective metrics models," Psychometrika, Springer;The Psychometric Society, vol. 37(4), pages 441-451, December.
    13. Ledyard Tucker & Samuel Messick, 1963. "An individual differences model for multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 28(4), pages 333-367, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Atsuho Nakayama & Daniel Baier, 2020. "Predicting brand confusion in imagery markets based on deep learning of visual advertisement content," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(4), pages 927-945, December.
    2. Daniel Baier & Sarah Frost, 2018. "Relating brand confusion to ad similarities and brand strengths through image data analysis and classification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 155-171, March.
    3. Giuseppe Bove & Akinori Okada, 2018. "Methods for the analysis of asymmetric pairwise relationships," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 5-31, March.
    4. Saburi, S. & Chino, N., 2008. "A maximum likelihood method for an asymmetric MDS model," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4673-4684, June.
    5. Ioan I. Gâf-Deac & Mohammad Jaradat & Florina Bran & Raluca Florentina Crețu & Daniel Moise & Svetlana Platagea Gombos & Teodora Odett Breaz, 2022. "Similarities and Proximity Symmetries for Decisions of Complex Valuation of Mining Resources in Anthropically Affected Areas," Sustainability, MDPI, vol. 14(16), pages 1-22, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giuseppe Bove & Akinori Okada, 2018. "Methods for the analysis of asymmetric pairwise relationships," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 5-31, March.
    2. Jacqueline Meulman & Peter Verboon, 1993. "Points of view analysis revisited: Fitting multidimensional structures to optimal distance components with cluster restrictions on the variables," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 7-35, March.
    3. Berrie Zielman & Willem Heiser, 1993. "Analysis of asymmetry by a slide-vector," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 101-114, March.
    4. J. Carroll, 1985. "Review," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 133-140, March.
    5. Herden, Gerhard & Pallack, Andreas, 2005. "Adequateness and interpretability of objective functions in ordinal data analysis," Journal of Multivariate Analysis, Elsevier, vol. 94(1), pages 19-69, May.
    6. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 7-67, March.
    7. Kohn, Hans-Friedrich, 2006. "Combinatorial individual differences scaling within the city-block metric," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 931-946, November.
    8. Saburi, S. & Chino, N., 2008. "A maximum likelihood method for an asymmetric MDS model," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4673-4684, June.
    9. Forrest Young & Yoshio Takane & Rostyslaw Lewyckyj, 1978. "Three notes on ALSCAL," Psychometrika, Springer;The Psychometric Society, vol. 43(3), pages 433-435, September.
    10. Willem Heiser, 1991. "A generalized majorization method for least souares multidimensional scaling of pseudodistances that may be negative," Psychometrika, Springer;The Psychometric Society, vol. 56(1), pages 7-27, March.
    11. de Leeuw, Jan & Mair, Patrick, 2009. "Multidimensional Scaling Using Majorization: SMACOF in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 31(i03).
    12. Jerzy Grobelny & Rafal Michalski & Gerhard-Wilhelm Weber, 2021. "Modeling human thinking about similarities by neuromatrices in the perspective of fuzzy logic," WORking papers in Management Science (WORMS) WORMS/21/09, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    13. Phipps Arabie, 1991. "Was euclid an unnecessarily sophisticated psychologist?," Psychometrika, Springer;The Psychometric Society, vol. 56(4), pages 567-587, December.
    14. Si-Tong Lu & Miao Zhang & Qing-Na Li, 2020. "Feasibility and a fast algorithm for Euclidean distance matrix optimization with ordinal constraints," Computational Optimization and Applications, Springer, vol. 76(2), pages 535-569, June.
    15. Yoshio Takane & J. Carroll, 1981. "Nonmetric maximum likelihood multidimensional scaling from directional rankings of similarities," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 389-405, December.
    16. Aurea Grané & Rosario Romera, 2018. "On Visualizing Mixed-Type Data," Sociological Methods & Research, , vol. 47(2), pages 207-239, March.
    17. Abe, Makoto, 1998. "Error structure and identification condition in maximum likelihood nonmetric multidimensional scaling," European Journal of Operational Research, Elsevier, vol. 111(2), pages 216-227, December.
    18. Michael W. Trosset, 2002. "Extensions of Classical Multidimensional Scaling via Variable Reduction," Computational Statistics, Springer, vol. 17(2), pages 147-163, July.
    19. Groenen, P.J.F. & Borg, I., 2013. "The Past, Present, and Future of Multidimensional Scaling," Econometric Institute Research Papers EI 2013-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. Warren Torgerson, 1986. "Scaling and Psychometrika: Spatial and alternative representations of similarity data," Psychometrika, Springer;The Psychometric Society, vol. 51(1), pages 57-63, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jclass:v:14:y:1997:i:2:p:195-224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.