Appendices
A
References
Introduction to Bayesian Statistics with R
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Preface
1
Getting Started
Introduction and Philosophy
2
The Bayesian Logic
3
Posterior estimation
4
Linear and linear mixed models
GLMMs, MS, Workflow
5
Bayesian model selection
6
Bayesian Workflow
7
Generalized linear mixed models
Hierachical models
8
Error in variable models
9
Occupancy models
10
State-space models
11
Autoregressive models
12
Integrated Models
13
Bayesian causal models
14
Process-based models
15
Approximate Bayesian Inference
Summary and conclusions
16
Summary and Conclusions
Appendices
A
References
B
Bayesian Numerics
C
Case Studies
Appendix A — References
George, Edward I., and Robert McCulloch. 1993.
“On Obtaining Invariant Prior Distributions.”
Journal of Statistical Planning and Inference
37 (2): 169–79.
https://doi.org/10.1016/0378-3758(93)90086-L
.
16
Summary and Conclusions
B
Bayesian Numerics