IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v37y2022i5d10.1007_s00180-022-01209-4.html
   My bibliography  Save this article

Nomclust 2.0: an R package for hierarchical clustering of objects characterized by nominal variables

Author

Listed:
  • Zdenek Sulc

    (Prague University of Economics and Business)

  • Jana Cibulkova

    (Prague University of Economics and Business)

  • Hana Rezankova

    (Prague University of Economics and Business)

Abstract

In this paper, we present the second generation of the nomclust R package, which we developed for the hierarchical clustering of data containing nominal variables (nominal data). The package completely covers the hierarchical clustering process, from dissimilarity matrix calculation, over the choice of a clustering method, to the evaluation of the final clusters. Through the whole clustering process, similarity measures, clustering methods, and evaluation criteria developed solely for nominal data are used, which makes this package unique. In the first part of the paper, the theoretical background of the methods used in the package is described. In the second part, the functionality of the package is demonstrated in several examples. The second generation of the package is completely rewritten to be more natural for the workflow of R users. It includes new similarity measures and evaluation criteria. We also added several graphical outputs and support for S3 generic functions. Finally, due to code optimizations, the calculation time of dissimilarity matrix calculation was substantially reduced.

Suggested Citation

  • Zdenek Sulc & Jana Cibulkova & Hana Rezankova, 2022. "Nomclust 2.0: an R package for hierarchical clustering of objects characterized by nominal variables," Computational Statistics, Springer, vol. 37(5), pages 2161-2184, November.
    • Handle: RePEc:spr:compst:v:37:y:2022:i:5:d:10.1007_s00180-022-01209-4
    DOI: 10.1007/s00180-022-01209-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-022-01209-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-022-01209-4?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Isabella Morlini & Sergio Zani, 2012. "A New Class of Weighted Similarity Indices Using Polytomous Variables," Journal of Classification, Springer;The Classification Society, vol. 29(2), pages 199-226, July.
    2. Zdeněk Šulc & Hana Řezanková, 2019. "Comparison of Similarity Measures for Categorical Data in Hierarchical Clustering," Journal of Classification, Springer;The Classification Society, vol. 36(1), pages 58-72, April.
    3. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    4. Linzer, Drew A. & Lewis, Jeffrey B., 2011. "poLCA: An R Package for Polytomous Variable Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i10).
    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. Bottai, Carlo & Crosato, Lisa & Domenech, Josep & Guerzoni, Marco & Liberati, Caterina, 2024. "Scraping innovativeness from corporate websites: Empirical evidence on Italian manufacturing SMEs," Technological Forecasting and Social Change, Elsevier, vol. 207(C).

    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. Adrian O’Hagan & Arthur White, 2019. "Improved model-based clustering performance using Bayesian initialization averaging," Computational Statistics, Springer, vol. 34(1), pages 201-231, March.
    2. Becken, Susanne & Stantic, Bela & Chen, Jinyan & Connolly, Rod M., 2022. "Twitter conversations reveal issue salience of aviation in the broader context of climate change," Journal of Air Transport Management, Elsevier, vol. 98(C).
    3. Orietta Nicolis & Jean Paul Maidana & Fabian Contreras & Danilo Leal, 2024. "Analyzing the Impact of COVID-19 on Economic Sustainability: A Clustering Approach," Sustainability, MDPI, vol. 16(4), pages 1-30, February.
    4. Lisa Blaydes, 2023. "Assessing the Labor Conditions of Migrant Domestic Workers in the Arab Gulf States," ILR Review, Cornell University, ILR School, vol. 76(4), pages 724-747, August.
    5. Jindřich Špička & Zdeňka Náglová, 2022. "Consumer segmentation in the meat market - The case study of Czech Republic," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(2), pages 68-77.
    6. Nicholas T. Davis & Kirby Goidel & Yikai Zhao, 2021. "The Meanings of Democracy among Mass Publics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(3), pages 849-921, February.
    7. Archana R. Panhalkar & Dharmpal D. Doye, 2020. "An approach of improving decision tree classifier using condensed informative data," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 47(4), pages 431-445, December.
    8. Carter, Virginia & Derudder, Ben & Henríquez, Cristián, 2021. "Assessing local governments’ perception of the potential implementation of biophilic urbanism in Chile: A latent class approach," Land Use Policy, Elsevier, vol. 101(C).
    9. Michele Cincera, 2005. "Firms' productivity growth and R&D spillovers: An analysis of alternative technological proximity measures," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(8), pages 657-682.
    10. Korneliusz Pylak & Piotr Oleszczuk & Przemysław Kowalik, 2021. "Typology of Smart Specializations Across European Regions," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 503-512.
    11. Assem Abu Hatab & Padmaja Ravula & Swamikannu Nedumaran & Carl-Johan Lagerkvist, 2022. "Perceptions of the impacts of urban sprawl among urban and peri-urban dwellers of Hyderabad, India: a Latent class clustering analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(11), pages 12787-12812, November.
    12. Horstmann, Felix, 2017. "Measuring the shopper's attitude toward the point of sale display: Scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 112-123.
    13. Junyong Jang & Yongbin Cho & Juntae Park, 2024. "Bus Route Sketching: A Multimetric Analysis from the User’s and Operator’s Perspectives," Sustainability, MDPI, vol. 16(16), pages 1-19, August.
    14. Elizaveta Zinovyeva & Raphael C. G. Reule & Wolfgang Karl Hardle, 2021. "Understanding Smart Contracts: Hype or Hope?," Papers 2103.08447, arXiv.org.
    15. Lorena Charrier & Paola Berchialla & Paola Dalmasso & Alberto Borraccino & Patrizia Lemma & Franco Cavallo, 2019. "Cigarette Smoking and Multiple Health Risk Behaviors: A Latent Class Regression Model to Identify a Profile of Young Adolescents," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1771-1782, August.
    16. Zhao, Yingrui & Hu, Songhua & Zhang, Ming, 2024. "Evaluating equitable Transit-Oriented development (TOD) via the Node-Place-People model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 185(C).
    17. Raphaela Grafiadeli & Heide Glaesmer & Birgit Wagner, 2022. "Loss-Related Characteristics and Symptoms of Depression, Prolonged Grief, and Posttraumatic Stress Following Suicide Bereavement," IJERPH, MDPI, vol. 19(16), pages 1-10, August.
    18. Guangchao Feng, 2014. "Estimating intercoder reliability: a structural equation modeling approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2355-2369, July.
    19. Paolo Brunori & Alain Trannoy & Caterina Francesca Guidi, 2021. "Ranking populations in terms of inequality of health opportunity: A flexible latent type approach," Health Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 358-383, February.
    20. Chester Harris, 1955. "Characteristics of two measures of profile similarity," Psychometrika, Springer;The Psychometric Society, vol. 20(4), pages 289-297, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:spr:compst:v:37:y:2022:i:5:d:10.1007_s00180-022-01209-4. 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.