Name / Position
AKASHI, Fumiya / Assistant Professor
|March 2015||Doctor of Science, Waseda University|
|March 2013||Master of Science, Waseda University|
|March 2011||Bachelor of Engineering, Waseda University|
|April 2019||Assistant Professor, Graduate School of Economics, University of Tokyo|
|April 2018||Assistant Professor, Research Institute for Science & Engineering, Waseda University|
|April 2017||Assistant Professor, Department of Applied Mathematics, Waseda University|
|April 2016||Research Associate, Department of Applied Mathematics, Waseda University|
|April 2015||Research Fellow-PD, Japan Society for the Promotion of Science|
|April 2014||Research Fellow-DC2, Japan Society for the Promotion of Science|
Mathematical statistics, Time series analysis
My research focuses on statistical inference for infinite variance and long-memory time series models. I am interested in robust estimation procedures based on the empirical likelihood method, self-normalization/weighting approach for nonstandard data without additional scaling of statistics or estimation of nuisance parameters. I am also working on statistical analysis of directional data, which appears in analysis of wildfire orientation or seismic data analysis.
- Fumiya Akashi, Masanobu Taniguchi and Anna Clara Monti (2020). “Robust causality test of infinite variance processes”. Journal of Econometrics. Volume 216, Issue 1, pp.235-245.
- Fumiya Akashi, Holger Dette and Yan Liu (2018). “Change point detection in autoregressive models with no moment assumptions”. Journal of Time Series Analysis. Volume 39, pp.763-786.
- Fumiya Akashi, Shuyang Bai and Murad S. Taqqu. (2018). “Robust regression on stationary time series: a self-normalized resampling approach”. Journal of Time Series Analysis, Volume 39, pp.417-432.
- Fumiya Akashi, Hiroaki Odashima, Masanobu Taniguchi and Anna C. Monti (2018). “A new look at portmanteau tests”. Sankhya, Volume 80-A, Part 1, pp.121-137.
- Fumiya Akashi (2017). “Self-weighted generalized empirical likelihood methods for hypothesis testing in infinite variance ARMA models”. Statistical Inference for Stochastic Processes. 20(3), pp.291-313.
- Sho Shibuya, Fumiya Akashi and Taniguchi, M. (2015). “Nonparametric approach for Box-Cox transformed process”. Advances in Science, Technology and Environmentology. B12, 31-44.
- Fumiya Akashi, Yan Liu and Masanobu Taniguchi (2015). An empirical likelihood approach for symmetric alpha-stable process. Bernoulli. 21(4), pp.2093-2119.
- Fumiya Akashi (2014). “Empirical likelihood approach toward discriminant analysis for dynamics of stable processes”. Statistical Methodology. Volume 19, pp.25-43.
- Fumiya Akashi (2013). “An empirical likelihood approach for discriminant analysis of non-Gaussian vector stationary linear processes”. Scientiae Mathematicae Japonicae Online. e- 2013, pp.645-660.
Books and Monographs
- Yan Liu, Fumiya Akashi and Masanobu Taniguchi Empirical Likelihood and Quantile Methods for Time Series: Efficiency, Robustness, Optimality and Prediction. JSS Research Series in Statistics. Springer Singapore.
Other Professional Activities and Awards
Other Professional Activities and Services - Grants
- Apr. 2020 - Mar. 2024
JSPS Grant-in-Aid for Young Scientists “Statistical inference for nonstandard data via time varying processes, robust regression and directional statistics”
- Apr. 2016 - Mar. 2020
JSPS Grant-in-Aid for Young Scientists (B) “Robust nonparametric inference for infinite variance processes with self-normalized empirical likelihood methods”
- Apr. 2014 - Mar. 2016
Grant-in-Aid for JSPS Research Fellow “Empirical likelihood approach to discriminant analysis of infinite variance time series models”