Extension and Application of Statistical Models Based on Bregman Divergence
| Project/Area Number |
22700292
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Statistical science
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| Research Institution | Waseda University (2012)
Aoyama Gakuin University (2010-2011) |
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Principal Investigator |
FUJIMOTO Yu 早稲田大学, ナノ理工学研究機構, 研究員 (40434302)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 統計的学習理論 / 情報量 / 統計モデル / 独立性の一般化 / 情報基礎 / 機械学習 / 統計科学 / 統計的独立性 / 統計数学 / copula |
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| Research Abstract |
In this study, we focused on a class of statistical models associated with the Bregman divergence which achieves robust estimation in calculating statistics. We have proposed some methods for estimation of these models, and analyzed some properties from the viewpoint of application for data analysis. Particularly, we generalized the definition of statistical independence by using an extension of the multiplication rule between positive values; the extension is derived from the Bregman divergence. We have shown that the proposed statistical models based on generalized independence can be useful tools in practical data analysis by alleviating the conditional independence assumed in the conventional methods.
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Report
(4 results)
Research Products
(14 results)
