JavaScript seems to be disabled in your browser. For the best experience on our site, be sure to turn on Javascript in your browser.

Artículo: AMZ-B0DNJ2XZ4T

Bayesian Nonparametric Statistics: École d’Été de Probabilités de Saint-Flour LI - 2023 (Lecture Notes in Mathematics Book 2358)

Format:

Kindle

Kindle

Paperback

Detalles del producto

Disponibilidad
Sin stock

Peso con empaque
0.20 kg

Devolución
No

Condición
Nuevo

Producto de
Amazon

Viaja desde
USA

Sobre este producto

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.

Producto prohibido

Este producto no está disponible

Este producto viaja de USA

a tus manos en

Medios de pago

Conoce más detalles

Highlight, take notes, and search in the book In this edition, page numbers are just like the physical edition

Tarjetas de Débito, Crédito y Deuna