IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2006i3p1623-1642.html
   My bibliography  Save this article

Three-mode partitioning

Author

Listed:
  • Schepers, Jan
  • van Mechelen, Iven
  • Ceulemans, Eva

Abstract

No abstract is available for this item.

Suggested Citation

  • Schepers, Jan & van Mechelen, Iven & Ceulemans, Eva, 2006. "Three-mode partitioning," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1623-1642, December.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:3:p:1623-1642
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(06)00192-7
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. Lawrence Hubert & Phipps Arabie, 1985. "Comparing partitions," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 193-218, December.
    2. Pieter Kroonenberg & Jan Leeuw, 1980. "Principal component analysis of three-mode data by means of alternating least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(1), pages 69-97, March.
    3. Glenn Milligan, 1980. "An examination of the effect of six types of error perturbation on fifteen clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 325-342, September.
    4. Bock, Hans H., 1996. "Probabilistic models in cluster analysis," Computational Statistics & Data Analysis, Elsevier, vol. 23(1), pages 5-28, November.
    5. Paterlini, Sandra & Krink, Thiemo, 2006. "Differential evolution and particle swarm optimisation in partitional clustering," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1220-1247, March.
    6. Hand, David J. & Krzanowski, Wojtek J., 2005. "Optimising k-means clustering results with standard software packages," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 969-973, June.
    7. Anil Chaturvedi & J. Carroll, 1994. "An alternating combinatorial optimization approach to fitting the INDCLUS and generalized INDCLUS models," Journal of Classification, Springer;The Classification Society, vol. 11(2), pages 155-170, September.
    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. Doove, Lisa L. & Wilderjans, Tom F. & Calcagnì, Antonio & Van Mechelen, Iven, 2017. "Deriving optimal data-analytic regimes from benchmarking studies," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 81-91.
    2. Satoru Yokoyama & Atsuho Nakayama & Akinori Okada, 2009. "One-mode three-way overlapping cluster analysis," Computational Statistics, Springer, vol. 24(1), pages 165-179, February.
    3. van Dijk, A. & van Rosmalen, J.M. & Paap, R., 2009. "A Bayesian approach to two-mode clustering," Econometric Institute Research Papers EI 2009-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Eva Ceulemans & Iven Mechelen, 2008. "CLASSI: A classification model for the study of sequential processes and individual differences therein," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 107-124, March.
    5. Van Mechelen, Iven & Schepers, Jan, 2007. "A unifying model involving a categorical and/or dimensional reduction for multimode data," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 537-549, September.
    6. Romain Guigourès & Marc Boullé & Fabrice Rossi, 2018. "Discovering patterns in time-varying graphs: a triclustering approach," 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(3), pages 509-536, September.
    7. Jan Schepers & Eva Ceulemans & Iven Mechelen, 2008. "Selecting Among Multi-Mode Partitioning Models of Different Complexities: A Comparison of Four Model Selection Criteria," Journal of Classification, Springer;The Classification Society, vol. 25(1), pages 67-85, June.

    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. Michael Brusco & Douglas Steinley, 2007. "A Comparison of Heuristic Procedures for Minimum Within-Cluster Sums of Squares Partitioning," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 583-600, December.
    2. Pieter C. Schoonees & Patrick J. F. Groenen & Michel Velden, 2022. "Least-squares bilinear clustering of three-way data," 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. 16(4), pages 1001-1037, December.
    3. Aurora Torrente & Juan Romo, 2021. "Initializing k-means Clustering by Bootstrap and Data Depth," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 232-256, July.
    4. Pieter Schoonees & Michel Velden & Patrick Groenen, 2015. "Constrained Dual Scaling for Detecting Response Styles in Categorical Data," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 968-994, December.
    5. Michael Brusco & Douglas Steinley, 2015. "Affinity Propagation and Uncapacitated Facility Location Problems," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 443-480, October.
    6. Douglas Steinley & Michael Brusco, 2008. "Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 125-144, March.
    7. Florian Schreiber, 2017. "Identification of customer groups in the German term life market: a benefit segmentation," Annals of Operations Research, Springer, vol. 254(1), pages 365-399, July.
    8. Tom Wilderjans & Dirk Depril & Iven Van Mechelen, 2013. "Additive Biclustering: A Comparison of One New and Two Existing ALS Algorithms," Journal of Classification, Springer;The Classification Society, vol. 30(1), pages 56-74, April.
    9. Dolnicar, Sara & Grün, Bettina & Leisch, Friedrich, 2016. "Increasing sample size compensates for data problems in segmentation studies," Journal of Business Research, Elsevier, vol. 69(2), pages 992-999.
    10. Zaheer Ahmed & Alberto Cassese & Gerard Breukelen & Jan Schepers, 2023. "E-ReMI: Extended Maximal Interaction Two-mode Clustering," Journal of Classification, Springer;The Classification Society, vol. 40(2), pages 298-331, July.
    11. Julian Rossbroich & Jeffrey Durieux & Tom F. Wilderjans, 2022. "Model Selection Strategies for Determining the Optimal Number of Overlapping Clusters in Additive Overlapping Partitional Clustering," Journal of Classification, Springer;The Classification Society, vol. 39(2), pages 264-301, July.
    12. Chia-Yi Chiu & Jeffrey Douglas & Xiaodong Li, 2009. "Cluster Analysis for Cognitive Diagnosis: Theory and Applications," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 633-665, December.
    13. Weinand, J.M. & McKenna, R. & Fichtner, W., 2019. "Developing a municipality typology for modelling decentralised energy systems," Utilities Policy, Elsevier, vol. 57(C), pages 75-96.
    14. Iwin Leenen & Iven Mechelen & Paul Boeck, 2001. "Models for ordinal hierarchical classes analysis," Psychometrika, Springer;The Psychometric Society, vol. 66(3), pages 389-403, September.
    15. Laura Bocci & Donatella Vicari, 2019. "ROOTCLUS: Searching for “ROOT CLUSters” in Three-Way Proximity Data," Psychometrika, Springer;The Psychometric Society, vol. 84(4), pages 941-985, December.
    16. Eva Ceulemans & Iven Mechelen & Iwin Leenen, 2003. "Tucker3 hierarchical classes analysis," Psychometrika, Springer;The Psychometric Society, vol. 68(3), pages 413-433, September.
    17. Joeri Hofmans & Eva Ceulemans & Douglas Steinley & Iven Mechelen, 2015. "On the Added Value of Bootstrap Analysis for K-Means Clustering," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 268-284, July.
    18. Jukka Corander & Mats Gyllenberg & Timo Koski, 2009. "Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy," 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. 3(1), pages 3-24, June.
    19. Naoto Yamashita & Kohei Adachi, 2020. "A Modified k-Means Clustering Procedure for Obtaining a Cardinality-Constrained Centroid Matrix," Journal of Classification, Springer;The Classification Society, vol. 37(2), pages 509-525, July.
    20. Efthymios Costa & Ioanna Papatsouma & Angelos Markos, 2023. "Benchmarking distance-based partitioning methods for mixed-type data," 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. 17(3), pages 701-724, September.

    More about this item

    Statistics

    Access and download statistics

    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:eee:csdana:v:51:y:2006:i:3:p:1623-1642. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.