Developing distribution theory for discretely observed random field and its application to spatial statistics
| Project/Area Number |
23500353
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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 |
Statistical science
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| Research Institution | Kyushu University |
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Principal Investigator |
Ninomiya Yoshiyuki 九州大学, マス・フォア・インダストリ研究所, 准教授 (50343330)
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| Project Period (FY) |
2011-04-28 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | 確率場理論 / ゲノム科学 / スパース推定 / 多重検定 / 統計的漸近理論 / モデル選択 / 確率場 / 機械学習 / 情報量規準 / 正則化法 / 凸解析 / 変数選択 / 画像解析 / 関数データ解析 / 正規確率場 / 変化点解析 / ホットスポット / 確率値 / 検出力 / ステップダウン法 / 多重検定方式 / 対比較 / 超過確率 / 微分幾何 / QTL 解析 |
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| Outline of Final Research Achievements |
The main results are ``Development of a new multiplicity adjustment using spurious correlations'' and ``Derivation of AIC for regularization parameter selection in the LASSO.'' In the former, a new method is developed to improve the power of multiple tests, and the method is shown to be efficient in real data analysis. In the latter, for the LASSO in the framework of generalized linear models, an information criterion is derived as a unique criterion which has the same root as the classical criteria.
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Report
(6 results)
Research Products
(32 results)
