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Bayesian Nonparametric Statistics : École d’Été de Probabilités de Saint-Flour LI - 2023 / by Ismaël Castillo

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: École d'Été de Probabilités de Saint-Flour ; 2358Publisher: Cham : Springer Nature Switzerland, 2024Publisher: Cham : Imprint: Springer, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(XII, 216 p. 14 illus., 7 illus. in color.)ISBN:
  • 9783031740350
Subject(s): Additional physical formats: 9783031740343 | 9783031740367 | Erscheint auch als: 9783031740343 Druck-Ausgabe | Erscheint auch als: 9783031740367 Druck-AusgabeDDC classification:
  • 519.5 23
DOI: DOI: 10.1007/978-3-031-74035-0Online resources: Summary: -1. Introduction, rates I.-2. Rates II and first examples.-3. Adaptation I: smoothness.-4. Adaptation II: high-dimensions and deep neural networks -- 5. Bernstein-von Mises I: functionals -- 6. Bernstein-von Mises II: multiscale and applications -- 7. classification and multiple testing -- 8. Variational approximations.Summary: This up-to-date overview of Bayesian nonparametric statistics provides both an introduction to the field and coverage of recent research topics, including deep neural networks, high-dimensional models and multiple testing, Bernstein-von Mises theorems and variational Bayes approximations, many of which have previously only been accessible through research articles. Although Bayesian posterior distributions are widely applied in astrophysics, inverse problems, genomics, machine learning and elsewhere, their theory is still only partially understood, especially in complex settings such as nonparametric or semiparametric models. Here, the available theory on the frequentist analysis of posterior distributions is outlined in terms of convergence rates, limiting shape results and uncertainty quantification. Based on lecture notes for a course given at the St-Flour summer school in 2023, the book is aimed at researchers and graduate students in statistics and probability. .PPN: PPN: 1909519936Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS | ZDB-2-LNM
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