IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v46y2000i1p53-58.html
   My bibliography  Save this article

Uniform stability of posteriors

Author

Listed:
  • Basu, Sanjib

Abstract

Infinitesimal sensitivities of the posterior distribution P(·X) and posterior quantities [rho](P) w.r.t. the choice of the prior P are considered. In a very general setting, the posterior P(·x) and posterior quantities [rho](P) are treated as functions of the prior P on the space of probability measures. Stability then amounts to checking if these functions satisfy Lipschitz condition of order 1. For parametric prior families, an intuitive criterion of p-stability is proposed and a general result on p-stability of posteriors is established. This result is then used to show that exponential family priors produce p-stable posteriors. In another interesting development, the notion of uniform stability of posteriors, i.e., stability w.r.t. to the prior that hold uniformly over all data, is introduced. Sufficient conditions are obtained under which posteriors are uniformly stable in the total variation metric and the weak convergence metrics.

Suggested Citation

  • Basu, Sanjib, 2000. "Uniform stability of posteriors," Statistics & Probability Letters, Elsevier, vol. 46(1), pages 53-58, January.
  • Handle: RePEc:eee:stapro:v:46:y:2000:i:1:p:53-58
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(99)00086-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Bsau Sanjib, 1996. "Local Sensitivity, Functional Derivatives And Nonlinear Posterior Quantities," Statistics & Risk Modeling, De Gruyter, vol. 14(4), pages 405-418, April.
    2. Dey, Dipak K. & Birmiwal, Lea R., 1994. "Robust Bayesian analysis using divergence measures," Statistics & Probability Letters, Elsevier, vol. 20(4), pages 287-294, July.
    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. Haiyan Zheng & Thomas Jaki & James M.S. Wason, 2023. "Bayesian sample size determination using commensurate priors to leverage preexperimental data," Biometrics, The International Biometric Society, vol. 79(2), pages 669-683, June.
    2. Abhik Ghosh & Ayanendranath Basu, 2016. "Robust Bayes estimation using the density power divergence," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(2), pages 413-437, April.
    3. Luai Al-Labadi & Forough Fazeli Asl & Ce Wang, 2021. "Measuring Bayesian Robustness Using Rényi Divergence," Stats, MDPI, vol. 4(2), pages 1-18, March.
    4. Goh, Gyuhyeong & Dey, Dipak K., 2014. "Bayesian model diagnostics using functional Bregman divergence," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 371-383.
    5. Giles Hooker & Anand Vidyashankar, 2014. "Bayesian model robustness via disparities," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 556-584, September.
    6. Adriano Suzuki & Vicente Cancho & Francisco Louzada, 2016. "The Poisson–Inverse-Gaussian regression model with cure rate: a Bayesian approach and its case influence diagnostics," Statistical Papers, Springer, vol. 57(1), pages 133-159, March.
    7. Gyuhyeong Goh & Jae Kwang Kim, 2021. "Accounting for model uncertainty in multiple imputation under complex sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(3), pages 930-949, September.

    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:eee:stapro:v:46:y:2000:i:1:p:53-58. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.