Dedicated probabilistic modeling environments are also gaining ground and may become standard in the near future.
The holy grail is something like: feed in some data, or parameters and have an algorithm generate the corresponding correct Bayesian inference and posterior distribution. It's very easy for scientists, even with years of knowledge and experience, to implement things incorrectly ;)
The holy grail is something like: feed in some data, or parameters and have an algorithm generate the corresponding correct Bayesian inference and posterior distribution. It's very easy for scientists, even with years of knowledge and experience, to implement things incorrectly ;)
Check out Stan and Figaro:
http://mc-stan.org/
https://www.cra.com/technical-expertise/probabilistic-modeli...