Name: Masayo Y. Hirose
Position: Associate Professor
Affiliation: Institute of Mathematics for Industry, Kyushu University, Fukuoka, Japan
<Education>:
2014: Ph.D in Engineering: Graduate school of engineering science, Osaka university
Doctoral thesis: “An Empirical Best Linear Unbiased Predictor in Small Area Estimation via Adjusted Maximum Likelihood Method”
2010: Master in Engineering: Graduate school of engineering science, Osaka university
2008: Bachelor in Science: School of Science and Technology, Kwansei gakuin university
＊2011.8-2013.2: Visiting Ph.D. student, Joint Program in Survey Methodology, University of Maryland, USA (co-adviser of the doctoral thesis: Prof. Partha Lahiri)
<Employment>
2024.10--: Associate professor, Institute of Mathematics for Industry, Kyushu University
2019.4 --2024.9 : Assistant professor, Institute of Mathematics for Industry, Kyushu University
2016.4 -- 2019.3 : Assistant professor, Department of Data science, Institute of Statistical Mathematics
2015.6 -- 2016.3 : Assistant professor, School of Statistical Thinking, Institute of Statistical Mathematics
2014.4 -- 2015.5: Project assistant professor, Data Coordinating Center, Department of Medical Innovation, Osaka University Hospital
<Peer reviewed Paper>
1. Uno K, Yagi K, Yoshimori M, Tanigawa M, Yoshikawa T and Fujita S. (2013).
IFN production ability and healthy ageing: mixed model analysis of a 24 year longitudinal study in Japan.
BMJ Open, 3:e002113.
2. Yoshimori, M. and Lahiri, P. (2014).
A new adjusted maximum likelihood method for the Fay-Herriot small area model.
Journal of Multivariate Analysis, 124, 281-294.
3. Yoshimori, M. and Lahiri, P. (2014).
A second-order efficient empirical Bayes confidence interval.
The Annals of Statistics, 42, 1233-1261.
4. Yoshimori, M. (2015).
Numerical comparison between different prediction intervals using EBLUP under the Fay-Herriot model.
Communication in Statistics --Simulation and Computation, 44, 1158-1170.
5. Hirose, M.Y. (2017).
Non-area-specific adjustment factor for second-order efficient empirical Bayes confidence interval.
Computational Statistics & Data Analysis, 116, 67-78.
6. Takeuchi, D. et al. (16th author). (2017).
Impact of a Food Safety Campaign on Streptococcus suis Infection in Humans in Thailand,
The American Journal of Tropical Medicine and Hygiene, 96, 1370-1377.
7. Hirose, M.Y. and Lahiri, P. (2018).
Estimating Variance of Random Effects to Solve Multiple Problems Simultaneously.
The Annals of Statistics, 46, 1721 - 1741.
8. Hirose, M.Y., Park, Y. and Tsuchiya, T. (2018).
Analysis of a Disaster Prevention Consciousness Survey using a Small Area Explicit Model-based Approach,
Journal of the Japan Statistical Society (in Japanese), 48, 49-70
9. Hirose, M.Y. (2019),
A Class of General Adjusted Maximum likelihood Methods for Desirable Mean Squared Error Estimation of EBLUP under the Fay-Herriot Small Area Model,
Journal of Statistical Planning and Inference, 199, 302-310.
10. Hirose, M. Y., and Lahiri, P. (2021).
Multi-Goal Prior Selection: A Way to Reconcile Bayesian and Classical Approaches for Random Effects Models,
Journal of the American Statistical Association, 116, 1487-1497. (online published in 2020)
11. Hirose M.Y., Ghosh M., and Ghosh T. (2023)
Arc-Sin Transformation for Binomial Sample Proportions in Small Area Estimation.
Statistica Sinica, 33, 705-727.
12. Ghosh M., Ghosh T. and Hirose M.Y. (2022)
Poisson Counts, Square Root Transformation and Small Area Estimation,
Sankhya B, 84, p. 449–471.
13. Hirose M.Y. and Mano S. (2023)
Asymptotic UMVUE: Asymptotic Moments Matching the UMVUE under the Ewens
Sampling Formula,
Calcutta Statistical Association Bulletin, 75, 197-219.
14. Ho, K. L. K., Hirose, M. Y., Ghosh, M., and Kikuchi, K.
Small Area Estimation under Square Root Transformed Fay-Herriot Model with Functional Measurement Error in Covariates,
SankhyaB (online published in 2025)
<Awards>
1. Presentation award, poster session, in the annual meeting of the Japan Statistical Society in 2011.
2. Presentation award, competition session in the Japanese joint statistical meeting in 2012.