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integrated-inferences
CausalQueries:Make, Update, and Query Binary Causal Models
Users can declare causal models over binary nodes, update beliefs about causal types given data, and calculate arbitrary queries. Updating is implemented in 'stan'. See Humphreys and Jacobs, 2023, Integrated Inferences (<DOI: 10.1017/9781316718636>) and Pearl, 2009 Causality (<DOI:10.1017/CBO9780511803161>).
Maintained by Till Tietz. Last updated 1 months ago.
bayescausaldagsmixedmethodsstancpp
28 stars 9.02 score 54 scripts
flyaflya
causact:Fast, Easy, and Visual Bayesian Inference
Accelerate Bayesian analytics workflows in 'R' through interactive modelling, visualization, and inference. Define probabilistic graphical models using directed acyclic graphs (DAGs) as a unifying language for business stakeholders, statisticians, and programmers. This package relies on interfacing with the 'numpyro' python package.
Maintained by Adam Fleischhacker. Last updated 2 months ago.
bayesian-inferencedagsposterior-probabilityprobabilistic-graphical-modelsprobabilistic-programming
45 stars 6.97 score 52 scripts