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Introduction
Outline
Prerequisites
Key Concepts
Distributions
Prior
Likelihood
Posterior
P-values
Stan
Installing Stan
The Way of Stan/RStan
Elements of a Stan Program
Data
Transformed Data
Parameters
Transformed Parameters
Model
Generated Quantities
Using Stan
R
rstan
Data list
Debug model
Full model
Model summary
Diagnostics and beyond
rstanarm
brms
rethinking
Summary
Extensions
R
Stan functions
Other frameworks
Conclusion
References
Become a Bayesian with R & Stan
Michael Clark
Statistician Lead
2016-12-11
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