IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v008i20.html
   My bibliography  Save this article

deal: A Package for Learning Bayesian Networks

Author

Listed:
  • Boettcher, Susanne G.
  • Dethlefsen, Claus

Abstract

deal is a software package for use with R. It includes several methods for analysing data using Bayesian networks with variables of discrete and/or continuous types but restricted to conditionally Gaussian networks. Construction of priors for network parameters is supported and their parameters can be learned from data using conjugate updating. The network score is used as a metric to learn the structure of the network and forms the basis of a heuristic search strategy. deal has an interface to Hugin.

Suggested Citation

  • Boettcher, Susanne G. & Dethlefsen, Claus, 2003. "deal: A Package for Learning Bayesian Networks," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i20).
    • Handle: RePEc:jss:jstsof:v:008:i20
    DOI: http://hdl.handle.net/10.18637/jss.v008.i20
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v008i20/deal.pdf
    Download Restriction: no
    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v008i20/deal_1.2-4.tar.gz
    Download Restriction: no
    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v008.i20?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
    ---><---

    Citations

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


    Cited by:

    1. Carvalho, João Vinícius de França & Chiann, Chang, 2013. "Redes Bayesianas: Um método para avaliação de interdependência e contágio em séries temporais multivariadas," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(2), June.
    2. Scutari, Marco, 2017. "Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimized Implementations in the bnlearn R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i02).
    3. Michael J McGeachie & Hsun-Hsien Chang & Scott T Weiss, 2014. "CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data," PLOS Computational Biology, Public Library of Science, vol. 10(6), pages 1-7, June.
    4. Richard Howey & So-Youn Shin & Caroline Relton & George Davey Smith & Heather J Cordell, 2020. "Bayesian network analysis incorporating genetic anchors complements conventional Mendelian randomization approaches for exploratory analysis of causal relationships in complex data," PLOS Genetics, Public Library of Science, vol. 16(3), pages 1-35, March.
    5. repec:jss:jstsof:35:i03 is not listed on IDEAS
    6. Dethlefsen, Claus & Højsgaard, Søren, 2005. "A Common Platform for Graphical Models in R: The gRbase Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i17).
    7. Sagnik Datta & Ghislaine Gayraud & Eric Leclerc & Frederic Y. Bois, 2017. "Graph_sampler: a simple tool for fully Bayesian analyses of DAG-models," Computational Statistics, Springer, vol. 32(2), pages 691-716, June.
    8. repec:fgv:epgrbe:v:67:n:2:a:3 is not listed on IDEAS

    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:jss:jstsof:v:008:i20. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    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.