ENGLISH

Bayesian Modeling and Computation in Python

By Osvaldo A. Martin

Book information

Publisher
CRC Press
Year
2021
ISBN
9780367894368, 9781000520071, 9781032180298, 9781003019169
Language
english
Format
EPUB
Filesize
31 MB (32078738 bytes)
Series
Texts in Statistical Science
Pages
619\0
Orientation
landscape
Paginated
yes
Scanned
no
Time added
2024-09-24 13:34:10

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.

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