IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i15p2567-d869874.html
   My bibliography  Save this article

Preface to the Special Issue on “Bayesian Predictive Inference and Related Asymptotics—Festschrift for Eugenio Regazzini’s 75th Birthday”

Author

Listed:
  • Emanuele Dolera

    (Department of Mathematics, University of Pavia, Via Adolfo Ferrata 5, 27100 Pavia, Italy)

Abstract

It is my pleasure to write this Preface to the Special Issue of Mathematics entitled “Bayesian Predictive Inference and Related Asymptotics—Festschrift for Eugenio Regazzini’s 75th Birthday” [...]

Suggested Citation

  • Emanuele Dolera, 2022. "Preface to the Special Issue on “Bayesian Predictive Inference and Related Asymptotics—Festschrift for Eugenio Regazzini’s 75th Birthday”," Mathematics, MDPI, vol. 10(15), pages 1-4, July.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:15:p:2567-:d:869874
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/15/2567/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/15/2567/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patrizia Berti & Luca Pratelli & Pietro Rigo, 2021. "A Central Limit Theorem for Predictive Distributions," Mathematics, MDPI, vol. 9(24), pages 1-11, December.
    2. Federico Bassetti & Lucia Ladelli, 2021. "Mixture of Species Sampling Models," Mathematics, MDPI, vol. 9(23), pages 1-27, December.
    3. Eleonora Perversi & Eugenio Regazzini, 2015. "Inequality and risk aversion in economies open to altruistic attitudes," Papers 1507.00894, arXiv.org, revised May 2016.
    4. Sandra Fortini & Sonia Petrone & Hristo Sariev, 2021. "Predictive Constructions Based on Measure-Valued Pólya Urn Processes," Mathematics, MDPI, vol. 9(22), pages 1-19, November.
    5. Federico Bassetti & Eugenio Regazzini, 2005. "Asymptotic distribution and robustness of minimum total variation distance estimators," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 55-80.
    6. Alexander Gnedin & Zakaria Derbazi, 2022. "Trapping the Ultimate Success," Mathematics, MDPI, vol. 10(1), pages 1-19, January.
    7. Emanuele Dolera, 2022. "Asymptotic Efficiency of Point Estimators in Bayesian Predictive Inference," Mathematics, MDPI, vol. 10(7), pages 1-27, April.
    8. Bassetti, Federico & Bodini, Antonella & Regazzini, Eugenio, 2007. "Consistency of minimum divergence estimators based on grouped data," Statistics & Probability Letters, Elsevier, vol. 77(10), pages 937-941, June.
    9. Persi Diaconis, 2022. "Partial Exchangeability for Contingency Tables," Mathematics, MDPI, vol. 10(3), pages 1-12, January.
    10. Sandy Zabell, 2022. "Fisher, Bayes, and Predictive Inference," Mathematics, MDPI, vol. 10(10), pages 1-16, May.
    11. Lancelot F. James, 2022. "Single-Block Recursive Poisson–Dirichlet Fragmentations of Normalized Generalized Gamma Processes," Mathematics, MDPI, vol. 10(4), pages 1-10, February.
    12. Donato Cifarelli & Eugenio Regazzini, 1979. "A general approach to Bayesian analysis of nonparametric problems," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 2(1), pages 39-52, March.
    13. Bassetti, Federico & Bodini, Antonella & Regazzini, Eugenio, 2006. "On minimum Kantorovich distance estimators," Statistics & Probability Letters, Elsevier, vol. 76(12), pages 1298-1302, 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. Espen Bernton & Pierre E. Jacob & Mathieu Gerber & Christian P. Robert, 2019. "Approximate Bayesian computation with the Wasserstein distance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 235-269, April.
    2. Aude Geneway & Gabriel Peyré & Marco Cuturi, 2017. "Learning Generative Models with Sinkhorn Divergences," Working Papers 2017-83, Center for Research in Economics and Statistics.
    3. Morgan A. Schmitz & Matthieu Heitz & Nicolas Bonneel & Fred Ngolè & David Coeurjolly, 2017. "Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning," Working Papers 2017-84, Center for Research in Economics and Statistics.
    4. Manuel Arellano & Stéphane Bonhomme, 2023. "Recovering Latent Variables by Matching," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(541), pages 693-706, January.
    5. Bertram Düring & Lorenzo Pareschi & Giuseppe Toscani, 2018. "Kinetic models for optimal control of wealth inequalities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 91(10), pages 1-12, October.
    6. Bassetti, Federico & Bodini, Antonella & Regazzini, Eugenio, 2007. "Consistency of minimum divergence estimators based on grouped data," Statistics & Probability Letters, Elsevier, vol. 77(10), pages 937-941, June.
    7. Combes, Catherine & Ng, Hon Keung Tony, 2022. "On parameter estimation for Amoroso family of distributions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 191(C), pages 309-327.
    8. Shun-ichi Amari & Takeru Matsuda, 2022. "Wasserstein statistics in one-dimensional location scale models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(1), pages 33-47, February.
    9. Ali Amiryousefi & Ville Kinnula & Jing Tang, 2022. "Bayes in Wonderland! Predictive Supervised Classification Inference Hits Unpredictability," Mathematics, MDPI, vol. 10(5), pages 1-11, March.
    10. Antonio Lijoi & Igor Prünster, 2014. "Discussion of “On simulation and properties of the stable law” by L. Devroye and L. James," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 371-377, August.
    11. Persi Diaconis, 2023. "Approximate exchangeability and de Finetti priors in 2022," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 38-53, March.

    More about this item

    Keywords

    n/a;

    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:gam:jmathe:v:10:y:2022:i:15:p:2567-:d:869874. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.