| Project/Area Number |
21330049
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Economic statistics
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| Research Institution | Soka University (2010-2011)
Chuo University (2009) |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
FUJIKOSHI Yasunori 広島大学, 名誉教授 (40033849)
YAMAMOTO Taku 日本大学, 経済学部, 教授 (50104716)
KAMAKURA Toshinari 中央大学, 理工学部, 教授 (40150031)
KANO Yutaka 大阪大学, 基礎工学研究科, 教授 (20201436)
MURAKAMI Hidetoshi 防衛大学校, 専任講師 (60453677)
TUKADA Shinnichi 明星大学, 教育学部, 教授 (10319022)
TAKEDA Yuichi 神奈川工科大学, 教育センター, 准教授 (90349241)
SAKAORI Fumitake 中央大学, 理工学部, 准教授 (90386475)
国友 直人 東京大学, 経済学研究科, 教授 (10153313)
小西 貞則 九州大学, 数理学研究院, 教授 (40090550)
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| Co-Investigator(Renkei-kenkyūsha) |
KUNITOMO Naoto 東京大学, 経済学研究科 (10153313)
KONISHI Sadanori 中央大学, 理工学部, 教授 (40090550)
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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 |
¥10,010,000 (Direct Cost: ¥7,700,000、Indirect Cost: ¥2,310,000)
Fiscal Year 2011: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2010: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2009: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
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| Keywords | 高次元多変量データ / 高次元推測理論 / 高次元漸近理論 / 高次元モデリング手法 / シミュレーション / 計量経済統計 / 多変量モデル / 構造方程式モデル / 計量経済手法 / 尤度比統計量 / 高次元多変量解析 / 高次元モデリング / 共分散構造分析 / パネル構造方程式 / 非線形モデリング / ベイズ推定 / 潜在構造モデル / 正準相関係数 |
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| Research Abstract |
In multivariate analysis, it is important to develop the statistical method to analyze the high-dimensional data when the number of variables is large. In this study, we have also constructed a high-dimensional asymptotic theory for the traditional method when the number of variables is smaller than the number of observations. The aim of our study is to develop the introduction of high-dimensional method and the method of high-dimensional asymptotic theory when the number of variables is greater than the number of observations. We also applied our method and the statistical development of high-dimensional asymptotic theory in economics.
More specifically, the challenges of the following, we have achievements.
(1) Development of traditional multivariate methods for high-dimensional data
(2) Development of modern multivariate methods for high-dimensional data
(3) Development of high-dimensional modeling techniques
(4) Research and the applications based on statistical simulation
(5) Development and applications of high-dimensional statistical econometric
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