IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v103i484y2008p1508-1517.html
   My bibliography  Save this article

Bayesian Inference on Changes in Response Densities Over Predictor Clusters

Author

Listed:
  • Dunson, David B.
  • Herring, Amy H.
  • Siega-Riz, Anna Maria

Abstract

No abstract is available for this item.

Suggested Citation

  • Dunson, David B. & Herring, Amy H. & Siega-Riz, Anna Maria, 2008. "Bayesian Inference on Changes in Response Densities Over Predictor Clusters," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1508-1517.
    • Handle: RePEc:bes:jnlasa:v:103:i:484:y:2008:p:1508-1517
    as

    Download full text from publisher

    File URL: http://pubs.amstat.org/doi/abs/10.1198/016214508000001039
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Glen McGee & Ander Wilson & Thomas F. Webster & Brent A. Coull, 2023. "Bayesian multiple index models for environmental mixtures," Biometrics, The International Biometric Society, vol. 79(1), pages 462-474, March.
    2. Aßmann, Christian & Boysen-Hogrefe, Jens, 2011. "A Bayesian approach to model-based clustering for binary panel probit models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 261-279, January.
    3. Eric Coker & Robert Gunier & Asa Bradman & Kim Harley & Katherine Kogut & John Molitor & Brenda Eskenazi, 2017. "Association between Pesticide Profiles Used on Agricultural Fields near Maternal Residences during Pregnancy and IQ at Age 7 Years," IJERPH, MDPI, vol. 14(5), pages 1-20, May.
    4. Liverani, Silvia & Hastie, David I. & Azizi, Lamiae & Papathomas, Michail & Richardson, Sylvia, 2015. "PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i07).
    5. Silvia Liverani & Lucy Leigh & Irene L. Hudson & Julie E. Byles, 2021. "Clustering method for censored and collinear survival data," Computational Statistics, Springer, vol. 36(1), pages 35-60, March.
    6. Daniele Durante & Sally Paganin & Bruno Scarpa & David B. Dunson, 2017. "Bayesian modelling of networks in complex business intelligence problems," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 555-580, April.
    7. Joyee Ghosh & Amy H. Herring & Anna Maria Siega-Riz, 2011. "Bayesian Variable Selection for Latent Class Models," Biometrics, The International Biometric Society, vol. 67(3), pages 917-925, September.
    8. Aßmann, Christian & Boysen-Hogrefe, Jens, 2009. "A bayesian approach to model-based clustering for panel probit models," Economics Working Papers 2009-03, Christian-Albrechts-University of Kiel, Department of Economics.
    9. Ian C McDowell & Dinesh Manandhar & Christopher M Vockley & Amy K Schmid & Timothy E Reddy & Barbara E Engelhardt, 2018. "Clustering gene expression time series data using an infinite Gaussian process mixture model," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-27, January.
    10. Bruno Scarpa & David B. Dunson, 2014. "Enriched Stick-Breaking Processes for Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 647-660, June.
    11. Luke B. Smith & Brian J. Reich & Amy H. Herring & Peter H. Langlois & Montserrat Fuentes, 2015. "Multilevel quantile function modeling with application to birth outcomes," Biometrics, The International Biometric Society, vol. 71(2), pages 508-519, June.

    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:bes:jnlasa:v:103:i:484:y:2008:p:1508-1517. 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.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    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.