Development of statistical inference in small area estimation for developing countries and biometrics

2015 Fiscal Year Final Research Report

• Project/Area Number: 26880011
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Single-year Grants
• Research Field: Statistical science
• Research Institution: The Institute of Statistical Mathematics (2015); Osaka University (2014)
• Principal Investigator: Hirose Masayo 統計数理研究所, 大学共同利用機関等の部局等, 助教 (30739199)
• Research Collaborator: Partha Lahiri University of Maryland at College Park, JPSM, Professor
• Project Period (FY): 2014-08-29 – 2016-03-31
• Keywords: 小地域推定 / EBLUP / 予測誤差

Outline of Final Research Achievements

We have developed empirical best linear unbiased prediction approach (EBLUP) in small area estimation, both views from the perspective of point and interval estimation.
Firstly, we compared performances among certain EBLUPs have proposed recently. Secondly, our previous method for avoiding unrealistic predictive value applied to more general model than that of previous study was achieved in term of point estimation. Moreover, we also proposed new EBLUPs not only for the estimation of the mean squared error of EBLUP but also for the confidence interval.

Free Research Field

統計科学