dosearch

Identification of causal effects from arbitrary observational and experimental probability distributions via do-calculus and standard probability manipulations using a search-based algorithm by Tikka, Hyttinen and Karvanen (2021) doi:10.18637/jss.v099.i05. Allows for the presence of mechanisms related to selection bias (Bareinboim and Tian, 2015) doi:10.1609/aaai.v29i1.9679, transportability (Bareinboim and Pearl, 2014) http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf, missing data (Mohan, Pearl, and Tian, 2013) http://ftp.cs.ucla.edu/pub/stat_ser/r410.pdf and arbitrary combinations of these. Also supports identification in the presence of context-specific independence (CSI) relations through labeled directed acyclic graphs (LDAG). For details on CSIs see (Corander et al., 2019) doi:10.1016/j.apal.2019.04.004.

Last 30 days

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.