Novel tools of statistical analysis via their algebraic properties
| Project/Area Number |
24700288
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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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 |
Kobayashi Kei 統計数理研究所, 大学共同利用機関等の部局等, 助教 (90465922)
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| Project Period (FY) |
2012-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 代数統計学 / 漸近統計学 / 情報幾何学 / 高次元データ解析 / 漸近的統計理論 / 計算機代数 / 幾何学的統計学 / 漸近理論 / 統計的推測 / 国際情報交換 / ベイズ統計学 |
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| Outline of Final Research Achievements |
A class of novel algebraic estimators for algebraic models is proposed. We proposed an explicit method to compute the estimators and estimates by using computational algebraic methods. The estimators are defined by some lower-degree polynomial equations by holding some asymptotic statistical efficiency. This allows fast computation of the estimates. This research should be the first result evaluating and controlling trade-off between algebraic computation and statistical efficiency. Another result is a new permutation test for dendrograms by using their geometrical and algebraic structures. We tested difference between mental lexicons between groups of examinees by using the proposed method. The results of this research project have been published in several international conferences and journals.
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Report
(5 results)
Research Products
(42 results)
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[Journal Article] 日本人英語学習者の英語心内辞書の変容2015
Author(s)
折田充, 小林景, 村里泰昭, 神本忠光, 吉井誠, Richard S. Lavin, 相澤一美
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Journal Title
熊本大学社会文化研究
Volume: 13
Pages: 15-30
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Peer Reviewed / Acknowledgement Compliant
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[Presentation] Localized Centering: Reducing Hubness in Large-Sample Data2015
Author(s)
Hara, K., Suzuki, I., Shimbo, M., Kobayashi, K., Fukumizu, K. and Radovanovic, M.
Organizer
The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15)
Place of Presentation
Austin, Texias
Year and Date
2015-01-29
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