| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2012: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Outline of Final Research Achievements |
Sparse estimation via L1 regularization enables us to analyze the ultra high-dimeniosnal data, and it has been rapidly developed in the recent years. I made two research achievements in this project. First, I developed an efficient algorithm that estimates the tuning parameter in sparse regression modeling. Second, I proposed the L1 regularization procedure in the factor analysis model, and investigated the relationship between the traditional rotation technique and regularization procedure. I showed that the regularization is viewed as the generalization of the rotation method. I have also made a free software package in R (msgps and fanc).
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