| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Outline of Final Research Achievements |
In this program, I mainly conducted the following two pieces of research in the variable selection problem for linear mixed model, which is used in small area estimation.
First, I considered the covariate shift situation, which is when the values of covariates in the model for prediction differ from those in the model for observed data. Under the covariate shift situation, I constructed a variable selection criterion for linear mixed model based on the conditional AIC. Second, I considered variable selection and estimation simultaneously to minimize the total mean squared prediction errors of the predictor. The derived method can be regarded as an extension of the observed best prediction (OBP) method.
I also conducted research related to small area estimation or mixed effects model.
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