IDEAS home Printed from https://ideas.repec.org/a/bla/jorssb/v78y2016i5p1103-1130.html
   My bibliography  Save this article

A general framework for updating belief distributions

Author

Listed:
  • P. G. Bissiri
  • C. C. Holmes
  • S. G. Walker

Abstract

No abstract is available for this item.

Suggested Citation

  • P. G. Bissiri & C. C. Holmes & S. G. Walker, 2016. "A general framework for updating belief distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(5), pages 1103-1130, November.
    • Handle: RePEc:bla:jorssb:v:78:y:2016:i:5:p:1103-1130
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/rssb.12158
    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.

    References listed on IDEAS

    as
    1. Arnaud Doucet & Neil Shephard, 2012. "Robust inference on parameters via particle filters and sandwich covariance matrices," Economics Papers 2012-W05, Economics Group, Nuffield College, University of Oxford.
    2. Richard Royall & Tsung‐Shan Tsou, 2003. "Interpreting statistical evidence by using imperfect models: robust adjusted likelihood functions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(2), pages 391-404, May.
    3. Stephen Walker & Nils Lid Hjort, 2001. "On Bayesian consistency," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 811-821.
    4. repec:dau:papers:123456789/5724 is not listed on IDEAS
    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. Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
    2. Smith, Simon C. & Timmermann, Allan & Zhu, Yinchu, 2019. "Variable selection in panel models with breaks," Journal of Econometrics, Elsevier, vol. 212(1), pages 323-344.
    3. Zhiwei Zhang, 2010. "Profile Likelihood and Incomplete Data," International Statistical Review, International Statistical Institute, vol. 78(1), pages 102-116, April.
    4. George Karabatsos, 2023. "Approximate Bayesian computation using asymptotically normal point estimates," Computational Statistics, Springer, vol. 38(2), pages 531-568, June.
    5. Tsung-Shan Tsou, 2005. "Inferences of variance function - a parametric robust way," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(8), pages 785-796.
    6. Valen E. Johnson & David Rossell, 2010. "On the use of non‐local prior densities in Bayesian hypothesis tests," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 143-170, March.
    7. Shen, Chung-Wei & Tsou, Tsung-Shan & Balakrishnan, N., 2011. "Robust likelihood inference for regression parameters in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1696-1714, April.
    8. Ho, Chi-san & Damien, Paul & Walker, Stephen, 2017. "Bayesian mode regression using mixtures of triangular densities," Journal of Econometrics, Elsevier, vol. 197(2), pages 273-283.
    9. C Rohrbeck & D A Costain & A Frigessi, 2018. "Bayesian spatial monotonic multiple regression," Biometrika, Biometrika Trust, vol. 105(3), pages 691-707.
    10. Li, Yong & Liu, Xiao-Bin & Yu, Jun, 2015. "A Bayesian chi-squared test for hypothesis testing," Journal of Econometrics, Elsevier, vol. 189(1), pages 54-69.
    11. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Integrated Deviance Information Criterion for Latent Variable Models," Economics and Statistics Working Papers 6-2018, Singapore Management University, School of Economics.
    12. Lemonte, Artur J., 2013. "On the gradient statistic under model misspecification," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 390-398.
    13. Jeremy Fouliard & Michael Howell & Hélène Rey & Vania Stavrakeva, 2020. "Answering the Queen: Machine Learning and Financial Crises," NBER Working Papers 28302, National Bureau of Economic Research, Inc.
    14. Shively, Thomas S. & Walker, Stephen G. & Damien, Paul, 2011. "Nonparametric function estimation subject to monotonicity, convexity and other shape constraints," Journal of Econometrics, Elsevier, vol. 161(2), pages 166-181, April.
    15. Hoch, Jeffrey S. & Blume, Jeffrey D., 2008. "Measuring and illustrating statistical evidence in a cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 27(2), pages 476-495, March.
    16. Thomas S. Shively & Thomas W. Sager & Stephen G. Walker, 2009. "A Bayesian approach to non‐parametric monotone function estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 159-175, January.
    17. John Copas & Shinto Eguchi, 2010. "Likelihood for statistically equivalent models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 193-217, March.
    18. Caterina Conigliani & Andrea Tancredi, 2009. "A Bayesian model averaging approach for cost‐effectiveness analyses," Health Economics, John Wiley & Sons, Ltd., vol. 18(7), pages 807-821, July.
    19. Tsung-Shan Tsou, 2011. "Likelihood inferences for the link function without knowing the true underlying distributions," Computational Statistics, Springer, vol. 26(3), pages 507-519, September.
    20. Li, Yong & Yu, Jun & Zeng, Tao, 2018. "Specification tests based on MCMC output," Journal of Econometrics, Elsevier, vol. 207(1), pages 237-260.

    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:bla:jorssb:v:78:y:2016:i:5:p:1103-1130. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.