Bayesian networks : with examples in R
著者
書誌事項
Bayesian networks : with examples in R
（Texts in statistical science）（A Chapman & Hall book）
CRC Press, 2022
2nd ed
- : hbk
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注記
Bibliography: p. 251-256
Includes index
内容説明・目次
内容説明
Explains the material step-by-step starting from meaningful examples
Steps detailed with R code in the spirit of reproducible research
Real world data analyses from a Science paper reproduced and explained in
detail
Examples span a variety of fields across social and life sciences
Overview of available software in and outside R
目次
1. The Discrete Case: Multinomial Bayesian Networks. 2. The Discrete Case: Multinomial Bayesian Networks. 3. The Mixed Case: Conditional Gaussian Bayesian Networks. 4. Time Series: Dynamic Bayesian Networks. 5. More Complex Cases: General Bayesian Networks. 6. Theory and Algorithms for Bayesian Networks. 7. Software for Bayesian Networks. 8. Real-World Applications of Bayesian Networks.
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