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Title: GitHub - trocker/DBDA-python: Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

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https://patch-diff.githubusercontent.com/trocker/DBDA-python#doing-bayesian-data-analysis---pythonpymc3
PyMC3https://docs.pymc.io/
'Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan'https://sites.google.com/site/doingbayesiandataanalysis/
https://patch-diff.githubusercontent.com/trocker/DBDA-python/blob/master/Notebooks/images/DBDA2.png
Chapter 9 - Hierarchical Modelshttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%209.ipynb
Chapter 10 - Model Comparison and Hierarchical Modellinghttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2010.ipynb
Chapter 12 - Bayesian Approaches to Testing a Point ("Null") Hypothesishttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2012.ipynb
Chapter 16 - Metric-Predicted Variable on One or Two Groupshttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2016.ipynb
Chapter 17 - Metric-Predicted Variable with One Metric Predictorhttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2017.ipynb
Chapter 18 - Metric Predicted Variable with Multiple Metric Predictorshttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2018.ipynb
Chapter 19 - Metric Predicted Variable with One Nominal Predictorhttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2019.ipynb
Chapter 20 - Metric Predicted Variable with Multiple Nominal Predictorhttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2020.ipynb
Chapter 21 - Dichotomous Predicted Variablehttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2021.ipynb
Chapter 22 - Nominal Predicted Variablehttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2022.ipynb
Chapter 23 - Ordinal Predicted Variablehttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2023.ipynb
Chapter 24 - Count Predicted Variablehttp://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Chapter%2024.ipynb
Bayesian Linear Regression example (Bishop, 2006)http://nbviewer.jupyter.org/github/JWarmenhoven/Various-Machine-Learning-bits/blob/master/Bayesian%20Linear%20Regression.ipynb
Example on modelling Ordinal Data (Liddell & Kruschke, 2018)http://nbviewer.jupyter.org/github/JWarmenhoven/DBDA-python/blob/master/Notebooks/Ordinal%20Model_Kruschke_Liddell.ipynb
https://patch-diff.githubusercontent.com/trocker/DBDA-python#references
https://www.microsoft.com/en-us/research/people/cmbishop/https://www.microsoft.com/en-us/research/people/cmbishop/
https://sites.google.com/site/doingbayesiandataanalysis/https://sites.google.com/site/doingbayesiandataanalysis/
http://dx.doi.org/10.3758/s13423-016-1221-4http://dx.doi.org/10.3758/s13423-016-1221-4
http://dx.doi.org/10.3758/s13423-017-1272-1http://dx.doi.org/10.3758/s13423-017-1272-1
http://osf.io/3tkz4http://osf.io/3tkz4
https://doi.org/10.7717/peerj-cs.55https://doi.org/10.7717/peerj-cs.55
http://pymc-devs.github.io/pymc3/http://pymc-devs.github.io/pymc3/
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https://github.com/aloctavodia/Doing_bayesian_data_analysishttps://github.com/aloctavodia/Doing_bayesian_data_analysis
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