Statistical inference theory for irregularly spaced spatio-temporal data
| Project/Area Number |
25610030
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Foundations of mathematics/Applied mathematics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
YAJIMA Yoshihiro 東京大学, 経済学研究科(研究院), 教授 (70134814)
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| Project Period (FY) |
2013-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2014: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2013: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | 時空間統計解析 / 時空間定常確率場 / 統計的仮説検定 / 不等間隔時空間データ / 時空間計量経済学 / 大規模時空間データ / ノンパラメトリック検定 / セミパラメトリック検定 / 時空間非定常確率場 / 時空間統計的検定 |
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| Outline of Final Research Achievements |
We proposed a new test statistic for statistical hypothesis testing given irregularly spaced spatio-tempora data from a stationary random field.
If we assume that the limiting distribution under the null hypothesis is a normal distribution, its expectation and variance are expressed by a much simple form in terms of the kernel function that is used to construct an estimator of the spectral density function. Hence this statistic is applied easily to analyze an actual large spatio-temporal data. We are trying now to justify theoretically that the limiting distribution is normal.
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Report
(3 results)
Research Products
(8 results)
