2013 Fiscal Year Final Research Report
Improvement Theory of Nonparametric Statistical Precise Inference and Its Applications
| Project/Area Number |
21340026
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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 |
General mathematics (including Probability theory/Statistical mathematics)
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| Research Institution | Kyushu University |
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Principal Investigator |
MAESONO Yoshihiko 九州大学, 数理(科)学研究科(研究院), 教授 (30173701)
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| Co-Investigator(Kenkyū-buntansha) |
NISHII Ryuei 九州大学, マス・ファオ・インダストリ研究所, 教授 (40127684)
KONISHI Sadanori 中央大学, 理工学部, 教授 (40090550)
SAGAE Masahiko 金沢大学, 経済学経営学系, 教授 (20215669)
FUJII Yoshinori 宮崎大学, 教育文化学部, 教授 (10218985)
NINOMIYA Yoshiyuki 九州大学, マス・ファオ・インダストリ研究所, 准教授 (50343330)
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| Project Period (FY) |
2009-04-01 – 2014-03-31
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| Keywords | ノンパラメトリック / カーネル型推定量 / 情報量規準 / エッジワース展開 / 非線形判別 / ブートストラップ法 / ジャックナイフ法 / リサンプリング法 |
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| Research Abstract |
In this project, we obtain an higher order asymptotic properties for statistical inference based on resampling methods, which use the data repeatedly. We also obtain approximations of distribution functions of kernel type estimators, and applying these results, we propose new nonparametric test statistics. Furthermore, we develop an inference method based on Gaussian basic functions, which we can apply to non-linear complex systems. The non-linear regression model is studied precisely, and we obtain a flexible method which improve accuracy of statistical inferences for state space data.
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