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You’ll never guess what’s been happening with PyStan and PyMC—Click here to find out.

Andrew Gelman · published 15 October 2015

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https://www.python.org/dev/peps/pep-0020/
python.org
https://bob-carpenter.github.io
bob-carpenter.github.io
https://ariddell.org
ariddell.org
https://mc-stan.org/interfaces/shinystan.html
mc-stan.org
https://mc-stan.org
mc-stan.org
https://pymc-devs.github.io/pymc3/
pymc-devs.github.io
https://pymc-devs.github.io/pymc/
pymc-devs.github.io
https://groups.google.com/forum/
groups.google.com
https://en.wikipedia.org/wiki/Rao–Blackwell_theorem
en.wikipedia.org
https://headmyshoulder.github.io/odeint-v2/
headmyshoulder.github.io
https://github.com/pymc-devs/pymc3/issues/708
github.com
https://www.bayespy.org/intro.html
bayespy.org
https://www.stat.columbia.edu/~gelman/book/
stat.columbia.edu
https://www.stat.columbia.edu/~gelman/arm/
stat.columbia.edu
https://www.youtube.com/watch?v=qQFF4tPgeWI
youtube.com
https://www.youtube.com/watch?v=6NXRCtWQNMg
youtube.com
https://pyvideo.org/video/2760/bayesian-statistical-analysis-using-python-part-1
pyvideo.org
https://pyvideo.org/video/2759/bayesian-statistical-analysis-using-python-part-0
pyvideo.org
https://pyvideo.org/video/2758/bayesian-statistical-analysis-using-python-part-2
pyvideo.org
Frequentism and Bayesianism IV: How to be a Bayesian in Python
jakevdp.github.io
https://www.stat.columbia.edu/~gelman/research/unpublished/loo_stan.pdf
stat.columbia.edu
Elsewhere on statmodeling.stat.columbia.edu (2)