Kniha Bayesian Nonparametric Statistics Ismaël Castillo

Bayesian Nonparametric Statistics

École d'Été de Probabilités de Saint-Flour L - 2023

Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Springer, Berlin
Dostupnost: Skladem u dodavatele
Odesíláme za 5-8 dnů
1 489
This up-to-date overview of Bayesian nonparametric statistics provides both an introduction to the f...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2024
Stránek
206
EAN
9783031740343
Enbook ID
46582842
Vydavatel
Hmotnost
326
Rozměry
155 x 235

Kompletní popis

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. 

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