| Project/Area Number |
15200021
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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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 University of Tokyo |
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Principal Investigator |
YAJIMA Yoshihiro The University of Tokyo, Graduate School of Economics, Professor, 大学院経済学研究科, 教授 (70134814)
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| Co-Investigator(Kenkyū-buntansha) |
OGATA Yoshihiko Institute of Statistical Mathematics, Dep of Forecasting and Control, Professor, 統計数理研究所・調査実験解析研究系, 教授 (70000213)
KUBOKAWA Tatsuya The University of Tokyo, Graduate School of Economics, Professor, 大学院経済学研究科, 教授 (20195499)
NISHII Ryuei Kyushu University, Graduate School of Mathematics, Professor, 大学院数理学研究院, 教授 (40127684)
MATSUDA Yasumasa Tohoku University, Graduate School of Economics, Associate Professor, 大学院経済学研究科, 准教授 (10301590)
MARUYAMA Yuzo The University of Tokyo, Center of Spatial Information Science, Associate Professor, 空間情報科学研究センター, 准教授 (30304728)
間瀬 茂 東京工業大学, 大学院・情報理工学研究科, 教授 (70108190)
福重 元嗣 大阪大学, 大学院・経済学研究科, 助教授 (10208936)
大瀧 慈 広島大学, 原爆放射線医学研究所, 教授 (20110463)
清水 邦夫 慶應義塾大学, 理工学部, 教授 (60110946)
鎌倉 稔成 中央大学, 理工学部, 教授 (40150031)
吉田 あつし 筑波大学, 社会工学系, 教授 (60240272)
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| Project Period (FY) |
2003 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥48,750,000 (Direct Cost: ¥37,500,000、Indirect Cost: ¥11,250,000)
Fiscal Year 2006: ¥14,430,000 (Direct Cost: ¥11,100,000、Indirect Cost: ¥3,330,000)
Fiscal Year 2005: ¥14,430,000 (Direct Cost: ¥11,100,000、Indirect Cost: ¥3,330,000)
Fiscal Year 2004: ¥9,620,000 (Direct Cost: ¥7,400,000、Indirect Cost: ¥2,220,000)
Fiscal Year 2003: ¥10,270,000 (Direct Cost: ¥7,900,000、Indirect Cost: ¥2,370,000)
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| Keywords | Spatio-temporal random field / Markov random field / Spatio-temporal point process / Empirical Bayes estimator / Spatial competition / Spatial data analysis / Circular data analysis / Small area statistics / 空間フーリエ解析 / Echelon解析 / 角度データ解析 / 空間的分散不均一性 / 時空間相関分析 / 階層ベイズモデル / 経験ベイズモデル / Spatial AdaBoost / 確率伝播法 / クロスバリデーション法 / Space-time ETAS model / 時空間パネルデータ / 空間クラスタリング / クロスバリデーション / ノンパラメトリック解析 / 離散選択モデル / 空間商圏分析 / 球面分布 / 非線形回帰モデル / 空間ネットワーク / 空間分割 |
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| Research Abstract |
We held a research conference on spatio-temporal statistical analysis every year through the research period from 2003 to 2006. These conferences have made much contribution to the development of spatio-temporal statistical analysis in both theory and its applications and to that the researchers in this field are able to deepen the understanding of the topic and share the studies to be solved in future with each other.
We have conducted our research project by dividing the members into five groups. First for inference theory and applications of random fields, we proposed a generalization of Fourier analysis of time series to spatio-temporal data and applied it to analyze a land price data of Tokyo Metropolitan area. Secondly for inference theory and its applications of spatio-temporal point processes, we developed an intensity function taking into account of spatio and temporal correlations simultaneously and applied it to analyze earthquake data. Furthermore we developed a threshold method to predict the sample variance and applied it to analyze rainfall data. Spatio-temporal correlation analysis between epidemiological data was also conducted. Thirdly for inference theory and applications of large sample-size data, we developed a new methodology of dscriminat analysis on Markov random fields and Echelon method for detecting hot spots of spatial data. Fourthly for inference theory and its application of small area data, we developed minimax and empirical Bayes estimators, which are able to overcome multicolinearity, and are robust against the instability caused by small sample size data. Finally for inference theory and its applications of panel data, we conducted an empirical analysis of spatial competition and its equiburium. And we conducted simulation studies, which investigated spurious spatial correlation caused by autocorrelations within individual time series and spatial heteroskedasticity between individual time series.
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