| Budget Amount *help |
¥12,480,000 (Direct Cost: ¥9,600,000、Indirect Cost: ¥2,880,000)
Fiscal Year 2020: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2019: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2017: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2016: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
|
|---|
| Outline of Final Research Achievements |
The expected Euler characteristic method is a geometric method to approximate the distribution of the maximum of a random field. It is available for the adjustment of the multiplicity p-value in multiple comparisons including signal detection and change point analysis. For example, it is used as a standard tool in brain image data analysis. However, this method has some immature parts as a methodology; e.g., the evaluation of approximation errors has not been fully elucidated. There is also room for further practical improvements such as efficient numerical calculations. Furthermore, it is possible to explore boundaries with related mathematical fields such as the random matrix theory and the theory of algebraic statistics. In this study, we comprehensively study the expected Euler characteristic method from these viewpoints.
|
