Causal discovery in the presence of missing data
Missing data are ubiquitous in many domains such as healthcare. Depending on how they are missing, the (conditional) independence relations in the observed data may be different from those for the complete data generated by the underlying causal process (which are not fully observable) and, as a con...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2018
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233336 |