| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Outline of Final Research Achievements |
This study attempted to develop methods exploiting auxiliary variables in order to improve modeling accuracy of the primary variables. A selection method of useful auxiliary variables was developed in incomplete data analysis, where latent variables are included. The goodness of a model constructed by auxiliary variables is measured by an information criterion. A relationship between the proposed criterion and previous criteria was shown. This study also proposed a screening method used when the number of auxiliary variables are large, and derived an information criterion to select useful auxiliary variables under covariate shift.
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