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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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| 出版年: | Int J Data Sci Anal |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer International Publishing
2018
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6428307/ https://ncbi.nlm.nih.gov/pubmed/30957008 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s41060-018-0097-y |
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