| 紀錄類型: |
書目-電子資源
: Monograph/item
|
| 杜威分類號: |
519.5/42 |
| 書名/作者: |
Bayesian modeling and computation in Python/ Osvaldo A. Martin, Ravin Kumar and Junpeng Lao. |
| 作者: |
Martin, Osvaldo. |
| 其他作者: |
Kumar, Ravin. |
| 出版者: |
Boca Raton, FL : : CRC Press,, 2022. |
| 面頁冊數: |
1 online resource. |
| 附註: |
"A Chapman & Hall book." |
| 標題: |
Bayesian statistical decision theory. |
| 標題: |
Python (Computer program language) |
| 標題: |
Mathematical statistics. |
| ISBN: |
9781003019169 |
| ISBN: |
1003019161 |
| ISBN: |
9781000520040 |
| ISBN: |
1000520048 |
| ISBN: |
9781000520071 |
| ISBN: |
1000520072 |
| 書目註: |
Includes bibliographical references and index. |
| 摘要、提要註: |
"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"-- |
| 電子資源: |
https://www.taylorfrancis.com/books/9781003019169 |