IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v45y2018i11p2020-2038.html
   My bibliography  Save this article

Graphical models for complex networks: an application to Italian museums

Author

Listed:
  • Cristina Coscia
  • Roberto Fontana
  • Patrizia Semeraro

Abstract

This paper applies probabilistic graphical models in a new framework to study association rules driven by consumer choices in a network of Italian museums. The network consists of the museums participating in the programme of Abbonamento Musei Torino Piemonte, which is a yearly subscription managed by Associazione Torino Città Capitale Europea. It is available to people living in the Piemonte region, Italy. Consumers are card-holders, who are allowed entry to all the museums in the network for one year. We employ graphical models to highlight associations between the museums driven by card-holder visiting behaviour. We use both simple undirected graphs and more complex directed graphs, and we do not make any hypothesis on the models but rather learn their structures directly from the data. We also use methodologies and tools for robust network identification and principal component analysis to complete the analysis of the phenomenon.

Suggested Citation

  • Cristina Coscia & Roberto Fontana & Patrizia Semeraro, 2018. "Graphical models for complex networks: an application to Italian museums," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(11), pages 2020-2038, August.
  • Handle: RePEc:taf:japsta:v:45:y:2018:i:11:p:2020-2038
    DOI: 10.1080/02664763.2017.1406901
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2017.1406901
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2017.1406901?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.

    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:taf:japsta:v:45:y:2018:i:11:p:2020-2038. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.