WAIC and WBIC with Python Stan
100 Exercises for Building Logic
Published on 20. December 2023
XII, 242 pages
978-981-99-3841-4 (ISBN)
Description
Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you're a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.
The key features of this indispensable book include:
- A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.
- 100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.
- A comprehensive guide to Sumio Watanabe's groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.
- Detailed source programs and Stan codes that will enhance readers' grasp of the mathematical concepts presented.
- A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.
Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!
More details
Series
Edition
1st ed. 2023
Language
English
Place of publication
Singapore
Singapore
Publishing group
Springer Singapore
Product notice
Reflowable
Illustrations
XII, 242 p. 44 illus., 38 illus. in color.
File size
3,68 MB
ISBN-13
978-981-99-3841-4 (9789819938414)
DOI
10.1007/978-981-99-3841-4
Schweitzer Classification
Other editions
Additional editions
Book
12/2023
Springer
€53.49
Shipment within 3-4 weeks
Person
Joe Suzuki is a professor of statistics at Osaka University, Japan.
Content
Over view of Watanabe's Bayes.- Introduction to Watanabe Bayesian Theory.- MCMC and Stan.- Mathematical Preparation.- Regular Statistical Models.- Information Criteria.- Algebraic Geometry.- The Essence of WAOIC.- WBIC and Its Application to Machine Learning.
