dosearch : Causal Effect Identification from Multiple Incomplete Data Sources
Year of publication
2019
Authors
Tikka, Santtu; Hyttinen, Antti; Karvanen, Juha
Abstract
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 et al. (2021) . Allows for the presence of mechanisms related to selection bias (Bareinboim, E. and Tian, J. (2015) ), transportability (Bareinboim, E. and Pearl, J. (2014) ), missing data (Mohan, K. and Pearl, J. and Tian., J. (2013) ) 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) .
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Publication type
Publication format
Information and communication technology application
MINEDU's publication type classification code
I2 ICT applications
Publication channel information
Publisher
CRAN - The Comprehensive R Archive Network
Open access
Open access in the publisher’s service
Yes
Open access of publication channel
Fully open publication channel
Self-archived
No
Other information
Fields of science
Statistics and probability; Computer and information sciences
Keywords
[object Object],[object Object]
Internationality of the publisher
International
Language
English
International co-publication
No
Co-publication with a company
No
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes