| Budget Amount *help |
¥17,810,000 (Direct Cost: ¥13,700,000、Indirect Cost: ¥4,110,000)
Fiscal Year 2015: ¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2014: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2013: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2012: ¥7,020,000 (Direct Cost: ¥5,400,000、Indirect Cost: ¥1,620,000)
|
|---|
| Outline of Final Research Achievements |
Bootstrap method has a large approximation error for computing a confidence level by resampling from data. For computing confidence levels with higher accuracy, multiscale bootstrap method utilizes a scaling-law of probability when changing the sample size of data, and double bootstrap method adjusts the approximation error by resampling. In this research, multiscale double bootstrap method has been proposed by using these two existing approaches together. We proved that the new method further improves the accuracy. In terms of the geometry of the space of probability distributions, the approximation error of bootstrap is expressed as a “mean curvature” of the boundary surface of hypothesis, and that of double bootstrap is expressed as a “mean curvature of the mean curvature”, and they are removed by multiscale bootstrap.
|
