IDEAS home Printed from https://ideas.repec.org/a/spr/jclass/v8y1991i2p217-237.html
   My bibliography  Save this article

A new approach to isotonic agglomerative hierarchical clustering

Author

Listed:
  • Werner Vach
  • Paul Degens

Abstract

No abstract is available for this item.

Suggested Citation

  • Werner Vach & Paul Degens, 1991. "A new approach to isotonic agglomerative hierarchical clustering," Journal of Classification, Springer;The Classification Society, vol. 8(2), pages 217-237, December.
    • Handle: RePEc:spr:jclass:v:8:y:1991:i:2:p:217-237
    DOI: 10.1007/BF02616240
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02616240
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02616240?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. Glenn Milligan, 1979. "Ultrametric hierarchical clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 44(3), pages 343-346, September.
    2. Vladimir Batagelj, 1981. "Note on ultrametric hierarchical clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 46(3), pages 351-352, September.
    3. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    4. Lawrence Hubert, 1973. "Monotone invariant clustering procedures," Psychometrika, Springer;The Psychometric Society, vol. 38(1), pages 47-62, March.
    Full references (including those not matched with items on IDEAS)

    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. William Day & Herbert Edelsbrunner, 1985. "Investigation of proportional link linkage clustering methods," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 239-254, December.
    2. Edmund Peay, 1975. "Nonmetric grouping: Clusters and cliques," Psychometrika, Springer;The Psychometric Society, vol. 40(3), pages 297-313, September.
    3. Nathanaël Randriamihamison & Nathalie Vialaneix & Pierre Neuvial, 2021. "Applicability and Interpretability of Ward’s Hierarchical Agglomerative Clustering With or Without Contiguity Constraints," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 363-389, July.
    4. Pierre Hansen & Brigitte Jaumard & Bruno Simeone, 1996. "Espaliers: A generalization of dendrograms," Journal of Classification, Springer;The Classification Society, vol. 13(1), pages 107-127, March.
    5. Roy D'Andrade, 1978. "U-statistic hierarchical clustering," Psychometrika, Springer;The Psychometric Society, vol. 43(1), pages 59-67, March.
    6. Katarzyna Hampel & Paulina Ucieklak-Jez & Agnieszka Bem, 2021. "Health System Responsiveness in the Light of the Euro Health Consumer Index," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 659-667.
    7. Kim, Junyung & Shah, Asad Ullah Amin & Kang, Hyun Gook, 2020. "Dynamic risk assessment with bayesian network and clustering analysis," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    8. David G Mets & Michael S Brainard, 2018. "An automated approach to the quantitation of vocalizations and vocal learning in the songbird," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-29, August.
    9. Noah E. Friedkin, 1984. "Structural Cohesion and Equivalence Explanations of Social Homogeneity," Sociological Methods & Research, , vol. 12(3), pages 235-261, February.
    10. David Matesanz Gomez & Guillermo J. Ortega & Benno Torgler, 2011. "Measuring globalization: A hierarchical network approach," CREMA Working Paper Series 2011-11, Center for Research in Economics, Management and the Arts (CREMA).
    11. Balepur, Prashant Narayan, 1998. "Impacts of Computer-Mediated Communication on Travel and Communication Patterns: The Davis Community Network Study," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6cb1f85c, Institute of Transportation Studies, UC Berkeley.
    12. Lisa Price, 2001. "Demystifying farmers' entomological and pest management knowledge: A methodology for assessing the impacts on knowledge from IPM-FFS and NES interventions," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 18(2), pages 153-176, June.
    13. Elisa Frutos-Bernal & Ángel Martín del Rey & Irene Mariñas-Collado & María Teresa Santos-Martín, 2022. "An Analysis of Travel Patterns in Barcelona Metro Using Tucker3 Decomposition," Mathematics, MDPI, vol. 10(7), pages 1-17, March.
    14. Geert Soete & Wayne DeSarbo & J. Carroll, 1985. "Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm," Journal of Classification, Springer;The Classification Society, vol. 2(1), pages 173-192, December.
    15. Teh, Boon Kin & Goo, Yik Wen & Lian, Tong Wei & Ong, Wei Guang & Choi, Wen Ting & Damodaran, Mridula & Cheong, Siew Ann, 2015. "The Chinese Correction of February 2007: How financial hierarchies change in a market crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 225-241.
    16. 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.
    17. Wentao Qu & Xianchao Xiu & Huangyue Chen & Lingchen Kong, 2023. "A Survey on High-Dimensional Subspace Clustering," Mathematics, MDPI, vol. 11(2), pages 1-39, January.
    18. Taggart, J. H., 1999. "MNC subsidiary performance, risk, and corporate expectations," International Business Review, Elsevier, vol. 8(2), pages 233-255, April.
    19. Sorin Alexandru Ungureanu & Diana Andreea Mandricel & Bogdan Ioan Coculescu & Ionica Oncioiu, 2020. "Prevention in Dental Medicine. Case Studies and Explanations Regarding the Cost-Benefit Ratio," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 6(2), pages 135-147, June.
    20. Fang, Yixin & Wang, Junhui, 2011. "Penalized cluster analysis with applications to family data," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2128-2136, June.

    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:8:y:1991:i:2:p:217-237. 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.