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Estimating bounds on causal effects in high-dimensional and possibly confounded systems
We present an algorithm for estimating bounds on causal effects from observational data which combines graphical model search with simple linear regression. We assume that the underlying system can be represented by a linear structural equation model with no feedback, and we allow for the possibilit...
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| Publicado no: | Int J Approx Reason |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5711475/ https://ncbi.nlm.nih.gov/pubmed/29203954 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ijar.2017.06.005 |
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