Osvaldo A Martin

(Author)

Bayesian Modeling and Computation in PythonHardcover, 29 December 2021

Bayesian Modeling and Computation in Python
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Part of Series
Chapman & Hall/CRC Texts in Statistical Science
Print Length
398 pages
Language
English
Publisher
CRC Press
Date Published
29 Dec 2021
ISBN-10
036789436X
ISBN-13
9780367894368

Description

Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory.

The book starts with a refresher of the Bayesian Inference concepts. The second chapter introduces modern methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian Computation, end to end case studies showing how to apply Bayesian modelling in different settings, and a chapter about the internals of probabilistic programming languages. Finally the last chapter serves as a reference for the rest of the book by getting closer into mathematical aspects or by extending the discussion of certain topics.

This book is written by contributors of PyMC3, ArviZ, Bambi, and Tensorflow Probability among other libraries.

Product Details

Authors:
Osvaldo A MartinRavin KumarJunpeng Lao
Book Format:
Hardcover
Country of Origin:
US
Date Published:
29 December 2021
Dimensions:
25.4 x 17.78 x 2.39 cm
ISBN-10:
036789436X
ISBN-13:
9780367894368
Language:
English
Location:
Oxford
Pages:
398
Publisher:
Weight:
943.47 gm

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