Case Studies in Applied Bayesian Data Science
CIRM Jean-Morlet Chair, Fall 2018
Editors: Mengersen, Kerrie, Pudlo, Pierre, Robert P., Christian (Eds.)
Free Preview- Presents a survey of state of the art aspects of applied Bayesian data science
- Presents real-world case studies in applied Bayesian data science in the fields of health and ecology
- Introduces new methodologies
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- About this book
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Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor.
The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields. While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution.
The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration.
- Table of contents (17 chapters)
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Introduction
Pages 3-15
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A Survey of Bayesian Statistical Approaches for Big Data
Pages 17-44
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Bayesian Neural Networks: An Introduction and Survey
Pages 45-87
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Markov Chain Monte Carlo Algorithms for Bayesian Computation, a Survey and Some Generalisation
Pages 89-119
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Bayesian Variable Selection
Pages 121-135
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Table of contents (17 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Case Studies in Applied Bayesian Data Science
- Book Subtitle
- CIRM Jean-Morlet Chair, Fall 2018
- Editors
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- Kerrie Mengersen
- Pierre Pudlo
- Christian Robert P.
- Series Title
- Lecture Notes in Mathematics
- Series Volume
- 2259
- Copyright
- 2020
- Publisher
- Springer International Publishing
- Copyright Holder
- The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-42553-1
- DOI
- 10.1007/978-3-030-42553-1
- Softcover ISBN
- 978-3-030-42552-4
- Series ISSN
- 0075-8434
- Edition Number
- 1
- Number of Pages
- VI, 420
- Number of Illustrations
- 16 b/w illustrations, 94 illustrations in colour
- Additional Information
- Jointly published with Société Mathématique de France (SMF); sold and distributed to its memebers by the SMF, http://smf.emath.fr; ISBN SMF: [to follow]
- Topics
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