2015 Fiscal Year Final Research Report
Theoretical considerations of model selection method based on a minimization of an information criterion
Project/Area Number |
25540012
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Research Category |
Grant-in-Aid for Challenging Exploratory Research
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Allocation Type | Multi-year Fund |
Research Field |
Statistical science
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Research Institution | Hiroshima University |
Principal Investigator |
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Co-Investigator(Renkei-kenkyūsha) |
FUJISAWA HIRONORI 統計数理研究所, 数理・推論研究系, 教授 (00301177)
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) |
2013-04-01 – 2016-03-31
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Keywords | モデル選択 / 情報量規準 / 多変量線形回帰モデル / 高次元データ |
Outline of Final Research Achievements |
In this research, we study model selection method based on a minimization of an information criterion. There are many information criteria. We evaluate theoretical properties of an information criterion used for model selection by a large sample asymptotic theory such that the sample size goes to infinity and a high-dimensional and large sample asymptotic theory such that the sample size and the dimension of a vector of response variables go to infinity simultaneously. From obtained results, we provide standards of judgment with regard to deciding an information criterion.
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Free Research Field |
統計科学
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