An Introduction to Bayesian Inference, Methods and Computation
These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advance...
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| Format: | eBook |
| Language: | English |
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Cham
Springer International Publishing
2021, 2021
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| Edition: | 1st ed. 2021 |
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| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Uncertainty and Decisions
- Prior and Likelihood Representation
- Graphical Modeling
- Parametric Models
- Computational Inference
- Bayesian Software Packages
- Model choice
- Linear Models
- Nonparametric Models
- Nonparametric Regression
- Clustering and Latent Factor Models
- Conjugate Parametric Models