First version of exaustive search minimal admissable sets that satisfy the back door criterion.
It is based on a d-separation function from pgmpy package (https://github.com/pgmpy/pgmpy). It implements an algorithm found in "Probabilistic Graphical Models: Principles and Techniques" - Koller and Friedman. Is it possible to integrate that piece of code giving the proper credit to the coders? ( That packagee is under MIT License but I do not know much about licenses)
I have also found a polinomial time version of the minimal admissable sets algorithm described in https://arxiv.org/abs/1202.3764 by Johannes Textor and implementedin his cool project DAGitty (http://www.dagitty.net/dags.html) which is a javascript browser-based causal inference analyzer.
At the last minute I realized that you use different naming conventions for functions while I use camelCase naming convention. I can change that later if the rest of the code is ok.
First version of exaustive search minimal admissable sets that satisfy the back door criterion.
It is based on a d-separation function from pgmpy package (https://github.com/pgmpy/pgmpy). It implements an algorithm found in "Probabilistic Graphical Models: Principles and Techniques" - Koller and Friedman. Is it possible to integrate that piece of code giving the proper credit to the coders? ( That packagee is under MIT License but I do not know much about licenses)
I have also found a polinomial time version of the minimal admissable sets algorithm described in https://arxiv.org/abs/1202.3764 by Johannes Textor and implementedin his cool project DAGitty (http://www.dagitty.net/dags.html) which is a javascript browser-based causal inference analyzer.
At the last minute I realized that you use different naming conventions for functions while I use camelCase naming convention. I can change that later if the rest of the code is ok.