Constraint-based causal discovery with mixed data

We address the problem of constraint-based causal discovery with mixed data types, such as (but not limited to) continuous, binary, multinomial, and ordinal variables. We use likelihood-ratio tests based on appropriate regression models and show how to derive symmetric conditional independence tests...

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Detalles Bibliográficos
Autores principales: Tsagris, Michail, Borboudakis, Giorgos, Lagani, Vincenzo, Tsamardinos, Ioannis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Regular Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428307/
https://www.ncbi.nlm.nih.gov/pubmed/30957008
http://dx.doi.org/10.1007/s41060-018-0097-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428307/
https://www.ncbi.nlm.nih.gov/pubmed/30957008
http://dx.doi.org/10.1007/s41060-018-0097-y

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