Fast numerical computation for multivariate distributions with combinatorial structure and its application to spatial epidemiology
| Project/Area Number |
21500288
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | The Institute of Statistical Mathematics |
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Principal Investigator |
KURIKI Satoshi 統計数理研究所, 数理・推論研究系, 教授 (90195545)
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| Co-Investigator(Renkei-kenkyūsha) |
TAKAHASHI Kunihiko 国立保健医療科学院, 技術評価部, 研究員 (50323259)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2011: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2010: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2009: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 空間疫学 / スキャン統計 / コーダルグラフ / 多重検定 / スキャン統計量 |
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| Research Abstract |
In spatial epidemiology, it is important to evaluate the multiplicity-adjusted p-value of scan statistics by taking their spatial correlations into account. However, it is difficult to conduct exact numerical calculation because high-dimensional integrations are required. On the other hand, Monte Carlo simulations cannot yield precise results. In our proposed method, we represent the spatial correlations of scan statistics as a graph, and by extracting its Markov structure, rewrite the high-dimensional integration as a successive numerical integration. Although, the proposed method reduces computational time of integration drastically, it is not powerful enough for the real datasets. More research is needed for practical use.
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Report
(4 results)
Research Products
(9 results)
