Shintaro HASHIMOTO (橋本 真太郎)
Associate Professor
Department of Mathematics, Hiroshima University,
1-7-1, Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8521, JAPAN
Email: s-hashimoto(at)hiroshima-u.ac.jp
I am a member of
ISBA (International Society for Bayesian Analysis),
MJS (Mathematical Society of Japan) and
JSS (Japan Statsitical Society).
Research Interests
- Bayesian inference
- Higher order asymptotic theory
- Information inequalities
- Monte Carlo methods
- Non-regular statistical models
Education
- 2015 Ph.D. Department of Mathematics, University of Tsukuba, Japan
- 2013 M.A. Department of Mathematics, University of Tsukuba, Japan
- 2011 B.A. Department of Mathematics, University of Tsukuba, Japan
Preprints
- Nishina, S., Onizuka, T. and Hashimoto, S. (2026). Global-local shrinkage priors for modeling random effects in multivariate spatial small area estimation. Submitted. R-code, arXiv.
- Iwashige, F., Wakayama, T., Sugasawa, S. and Hashimoto, S. (2025). On misspecified error distributions in Bayesian functional clustering: Consequences and remedies, arXiv.
- Iwashige, F. and Hashimoto, S. (2025). Bayesian mixture modeling using a mixture
of finite mixtures with normalized inverse Gaussian weights. Submitted. R-code, arXiv.
- Hamura, Y., Onizuka, T., Hashimoto, S. and Sugasawa, S. (2025). Robust Bayesian inference for censored survival models. Submitted. R-code, arXiv.
Publications
- Hashimoto, S. (2026). On invariant moment matching priors for Bayesian point prediction. Statistics and Probability Letters, 238, 110874, web (Open access).
- Onizuka, T. and Hashimoto, S. (2025). Robust Bayesian graphical modeling using γ-divergence. Journal of Multivariate Analysis. 209, 105461, R-code, arXiv, web.
- Hamura, Y., Onizuka, T., Hashimoto, S. and Sugasawa, S. (2024). Sparse Bayesian inference on gamma-distributed observations using shape-scale inverse-gamma mixtures. Bayesian Analysis, 19(1), 77-97. R-code, arXiv, web.
- Onizuka, T., Hashimoto, S. and Sugasawa, S. (2024). Locally adaptive spatial quantile smoothing: Application to monitoring crime density in Tokyo. Spatial Statistics, 59, 100793. R-code, arXiv, web.
- Onizuka, T., Iwashige, F. and Hashimoto, S. (2024). Bayesian boundary trend filtering. Computational Statistics and Data Analysis, 191, 107889. R-code, arXiv, web.
- Onizuka, T., Hashimoto, S. and Sugasawa, S. (2024). Fast and locally adaptive Bayesian quantile smoothing using calibrated variational approximations. Statistics and Computing, 34, article number: 15. R-code, arXiv, web.
- Kawakami, J. and Hashimoto, S. (2023). Approximate Gibbs sampler for Bayesian Huberized lasso. Journal of Statistical Computation and Simulation, 93(1), 128-162. arXiv, web.
- Hashimoto, S. (2021). Predictive probability matching priors for a certain non-regular model. Statistics and Probability Letters, 174, 109096. web.
- Hashimoto, S. (2021). Reference priors via α-divergence for a certain non-regular model in the presence of a nuisance parameter. Journal of Statistical Planning and Inference, 213, 162-178. web, Technical Report.
- Sugasawa, S. and Hashimoto, S. (2021). Robust Bayesian changepoint analysis in the presence of outliers. Proceedings of the 13th KES-IDT 2021 Conference (eds. Czarnowski, I., Howlett, R. J. & Jain, L. C.), Smart Innovation, Systems and Technologies, 469-478. web.
- Koike, K. and Hashimoto, S. (2021). Improvement of Bobrovsky-Mayor-Wolf-Zakai bound. Entropy, 23(2), 161. web
- Nakagawa, T. and Hashimoto, S. (2021). On default priors for robust Bayesian estimation with divergences. Entropy, 23(1), 29. arXiv, web.
- Hashimoto, S. and Sugasawa, S. (2020). Robust Bayesian regression with synthetic posterior distributions. Entropy, 22(6), 661. R-code, arXiv, web.
- Nakagawa, T. and Hashimoto, S. (2020). Robust Bayesian inference via γ-divergence, Communications in Statistics - Theory and Methods, 49(2), 343-360. web.
- Hashimoto, S. (2019). Moment matching priors for non-regular models, Journal of Statistical Planning and Inference, 203, 169-177. web, Technical Report.
- Hashimoto, S. (2017). Robust estimation for skew-normal distribution with location and scale parameters via log-regularly varying functions. International Journal of Statistics and Systems, 12(4), 813-822. web.
- Akahira, M., Hashimoto, S., Koike, K. and Ohyauchi, N. (2016). Second order asymptotic comparison of the MLE and MCLE for a two-sided truncated exponential family of distributions. Communications in Statistics - Theory and Methods, 45(19), 5637-5659. web.
- Hashimoto, S. and Koike, K. (2015). Bhattacharyya type information inequality for the Bayes risk. Communications in Statistics - Theory and Methods, 44(24), 5213-5524. web.
Grants
- Grant-in-Aid for Scientific Research (C), Grant Number: 25K07131, 2025-2029 (Principal Investigator)
- Grant-in-Aid for Scientific Research (A), Grant Number: 25H00546, 2025-2030 (Co-Investigator)
- Grant-in-Aid for Early-Career Scientists, Grant Number: 21K13835, 2021-2024 (Principal Investigator)
- Grant-in-Aid for Scientific Research (B), Grant Number: 21H00699, 2021-2024 (Co-Investigator)
- Grant-in-Aid for Scientific Research (C), Grant Number: 20K11702, 2020-2022 (Co-Investigator)
- Grant-in-Aid for Young Scientists (B), Grant Number: 17K14233, 2017-2020 (Principal Investigator)
- University of Tsukuba Basic Research Support Problem Type A, 360,000 yen, 2014-2015
Ph.D Students
- Takahiro Onizuka (2022-2024): He is currently working as a Lecturer at Graduate School of Social Sciences, Chiba University
- Fumiya Iwashige (2024-)
Information for Prospective International Students:
Before reaching out about graduate or non-degree research student positions under my supervision, you are required to review the instructions on the following page:
https://www.hiroshima-u.ac.jp/en/international/admissions
Note: Please refrain from contacting me directly. I will only respond if your research proposal is exceptionally compelling.
教育・研究・科研費 (in Japanese)
書籍
エッセイ・研究紹介など (in Japanese)
