| Project/Area Number |
17K07578
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Ecology/Environment
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| Research Institution | The Institute of Statistical Mathematics |
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Principal Investigator |
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2019: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 個体群動態 / 群集動態 / 状態空間モデル / ベイズ推定 / クローナル繁殖 / 標識調査 / 情報量規準 / 推移行列モデル / クラスター点過程 / 標識再捕獲調査 / パーム尤度法 / 非定常空間点過程 / ベイズ統計 / 行列モデル / 階層モデル / 空間点過程 / ネイマン・スコット過程 / WAIC / 観察モデル / 個体群 / 赤池情報量規準 / EIC |
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| Outline of Final Research Achievements |
Setting information criterion, observation model and approximated Bayesian computation as the three keywords, this study developed state space models in which a mathematical model is used for a state model and a statistical model is used for an observation model of field observations. For animals, for example, integrating capture-mark-recapture data under natural conditions and experimental results in a laboratory, two-species community dynamics was examined. For plants, integrating aboveground and belowground information into a state space model, population dynamics of a clonal plant was examined.
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| Academic Significance and Societal Importance of the Research Achievements |
異質な情報を一つの統計モデルに統合して定量的に分析する需要は、生態学に限らず様々な場面で強く求められている。本研究のような情報の統合の実例を積み上げることは、特定の分野を超えて統計手法の汎用性を高めていく効果をもたらす。
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