Formalization and automation for statistical causal inference
Project/Area Number |
16K12398
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Research Category |
Grant-in-Aid for Challenging Exploratory Research
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Allocation Type | Multi-year Fund |
Research Field |
Statistical science
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Research Institution | Yokohama City University (2018) Chiba University (2016-2017) |
Principal Investigator |
Wang Jinfang 横浜市立大学, データサイエンス学部, 教授 (10270414)
|
Project Period (FY) |
2016-04-01 – 2019-03-31
|
Project Status |
Completed (Fiscal Year 2018)
|
Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
Keywords | causal inference / conditional independence / formalization / cain / SSReflect / cell regression / Bayesian inference / coq/SSReflect / data science / ssreflect / predictive inference / transfer Regression / universal algebra / diabetes / 統計的因果推論 / 条件付き独立性 / Cain algebra / 形式化 / Coq/SSReflect |
Outline of Final Research Achievements |
(1)Proposed non-inferior tests for image-diagnosis based on cluster data and successfully showed the usefulness of the methods by simulation studies and applying the tests to patients with acute subarachnoid hemorrhage. (2) Proposed random effect models for combining data obtained by multiple raters. New confidence intervals are proposed for both sensitivity and specificity. (3) We carried out formalization of the algebraic system of cain proposed by Wang (2010) for manipulating statistical conditional independence using the proof assistant SSReflect.
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Academic Significance and Societal Importance of the Research Achievements |
理論と応用の両面において、統計的因果推論は極めて重要な問題である。本研究では、この問題を正面から挑戦し、独自の代数系を提案し、それに基づく条件付き独立性の形式化を行った。これにより、条件付き独立性に関する操作の半自動化・自動化の可能性を開いた。
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Report
(4 results)
Research Products
(15 results)