| [Education] |  |
|
| 1987 B.A. (Engineering), University of Tokyo | ||
| 1989 M.A. (Engineering), University of Tokyo | ||
| 1992 Ph.D. (Engineering), University of Tokyo | ||
| [Employment History] | ||
| 1992 Associate Researcher, Mitsubishi Research Institute, Inc. | ||
| 1994 Assistant Professor, Institute of Social Sciences, University of Tsukuba | ||
| 1999 Associate Professor, Institute of Social Sciences, University of Tsukuba | ||
| 2004 Professor, Graduate School of Economics, Hitotsubashi University | ||
[Fields of Specialization]
Statistics, Econometrics
[Present Research Themes]
Nonparametric estimation, Semiparametric estimation, Survival analysis, High-dimensional problems
[Language]
Japanese, English
[Major Publications]
- Minimax estimators in the Manova model for arbitrary quadratic loss and unknown covariance matrix. Journal of Multivariate Analysis, 36(1991), 113-120.
- Estimation of the mean by three stage procedure. Sequential Analysis, 11(1992), 73-89.
- Construction of a confidence interval by triple sampling. Sequential Analysis, 11(1992), 273-287.
- The effect of heteroscedasticity on the actual size of the Chow test. Journal of the Japan Statistical Society, 26 (1996), 127-134. (co-authored by A. Takemura) Available at https://doi.org/10.14490/jjss1995.26.127
- The CUSUM tests with nonparametric regression residuals. Journal of the Japan Statistical Society, 27 (1997), 45-63. Available at https://doi.org/10.14490/jjss1995.27.45
- Testing the goodness of fit of a linear model by kernel regression. Communications in Statistics-Theory and Methods, 27 (1998), 529-546.
- Sequential estimation of the marginal density function for a strongly mixing process. Sequential Analysis, 17(1998), 239-251.
- Root-n-consistent semiparametric estimation of partially linear models for weakly dependent observations. Communications in Statistics-Theory and Methods, 28 (1999), 2001-2020.
- Nonparametric estimation of a conditional quantile for α-mixing processes. Annals of the Institute of Statistical Mathematics, 52 (2000), 459-470.
- Nonparametric density estimation for a long-range dependent linear process. Annals of the Institute of Statistical Mathematics, 52 (2000), 599-611.
- Nonparametric estimation of the conditional median function for long-range dependent processes. Journal of the Japan Statistical Society, 30 (2000), 129-142. Available at https://doi.org/10.14490/jjss1995.30.129
- Quantile regression in varying coefficient models. Journal of Statistical Planning and Inference, 121(2004), 113-125.
- Nonparametric regression with current status data. Annals of the Institute of Statistical Mathematics, 56(2004), 49-72.
- Nonparametric regression in proportional hazards models. Journal of the Japan Statistical Society, 34(2004), 1-17.
- Estimation in additive Cox models by marginal integration. Annals of the Institute of Statistical Mathematics, 57(2005), 403-423. Available at https://hdl.handle.net/10086/14605
- Estimation in Partial Linear Models under Long-Range Dependence. Discussion Papers #2007-7, Graduate School of Economics, Hitotsubashi University. Available at https://hdl.handle.net/10086/17011
- Nonparametric density estimation for linear processes with infinite variance. Annals of the Institute of Statistical Mathematics, 61(2009), 413-439. Available at https://hdl.handle.net/10086/16959
- A limit theorem for sums of bounded functional of linear processes without finite mean. Probability and Mathematical Statistics, 29(2009), 337-351.
- Nonparametric regression for dependent data in the errors-in-variables problem. Journal of Statistical Planning and Inference, 140 (2010), 3409-3424.
- Nonparametric estimation of conditional medians for linear and related processes. Annals of the Institute of Statistical Mathematics, 62 (2010), 995-1021.
- Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors. Annals of the Institute of Statistical Mathematics, 65 (2013), 23-47.
(Global COE Hi-Stat Discussion Paper Series 157, Hitotsubashi University (2010). Available at https://hdl.handle.net/10086/18811) - Nonparametric LAD Cointegrating Regression. Journal of Multivariate Analysis, 117 (2013), 150-162.
(Global COE Hi-Stat Discussion Paper Series 207, Hitotsubashi University (2011). Available at https://hdl.handle.net/10086/19400) - Variable selection in Cox regression models with varying coefficients. (jointly worked with Wolfgang Karl Härdle), Journal of Statistical Planning and Inference, 148 (2014), 67-81. (SFB 649 Discussion Paper 2012-061, Humboldt-Universität zu Berlin, Germany (2012). Available at http://sfb649.wiwi.hu-berlin.de/fedc/discussionPapers.php)
- Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data. (jointly worked with Ming-Yen Cheng, Jialiang Li, and Heng Peng), Annals of Statistics, 42 (2014), 1819-1849. (Available at http://arxiv.org/abs/1308.3942)
- Discussion on “Varying Coefficient Regression Models: A Review and New Developments by B.U.Park et al.”, International Statistical Review, 83 (2015), 68-70. (Available at http://onlinelibrary.wiley.com/doi/10.1111/insr.v83.1/issuetoc)
- Forward variable selection for sparse ultra-high dimensional varying coefficient models. (jointly worked with CHENG Ming-Yen, ZHANG Jin-Ting), Journal of the American Statistical Association, 111 (2016), 1209-1221. (Available at http://www.tandfonline.com/doi/full/10.1080/01621459.2015.1080708) (Hitotsubashi Invited Fellow Program Discussion Paper Series 27, Hitotsubashi University (2015). Available at https://hdl.handle.net/10086/26895)
- Efficient estimation in semivarying coefficient models for longitudinal/clustered data. (jointly worked with CHENG Ming-Yen, LI Jialiang), Annals of Statistics (http://imstat.org/aos/), 44(5) (2016), 1988-2017. (Available at http://www1.econ.hit-u.ac.jp/honda/AOS1506-015R1A0.pdf)
- Variable selection and structure identification for varying coefficient Cox models. (jointly worked with Ryota Yabe), Journal of Multivariate Analysis, 161(2017), 103-122. (Discussion Papers #2016-05. Available at https://hdl.handle.net/10086/28268)
- Adaptively weighted group Lasso for semiparametric quantile regression models. (jointly worked with ING Ching-Kang, WU Wei-Ying), Bernoulli, 25(2019), 3311-3338. Available at http://dx.doi.org/10.3150/18-BEJ1091 (Discussion Papers #2017-04. Available at https://hdl.handle.net/10086/28459)
- The de-biased group Lasso estimation for varying coefficient models. Annals of the Institute of Statistical Mathematics, 73(2021), 3-29. Available at http://dx.doi.org/10.1007/s10463-019-00740-4 (Discussion Papers #2018-04. Available at https://hdl.handle.net/10086/30520)
- Forward Variable Selection for Sparse Ultra-High Dimensional Generalized Varying Coefficient Models. (jointly workd with Lin Chien-Tong), Japanese Journal of Statistics and Data Science, 4 (2021), 151-179. Available at http://dx.doi.org/10.1007/s42081-020-00090-z (Discussion Papers #2020-01, Graduate School of Economics, Hitotsubashi University. Available at https://hdl.handle.net/10086/30969)
- Forward variable selection for ultra-high dimensional quantile regression models. (jointly worked with Lin Chien-Tong), Annals of the Institute of Statistical Mathematics, 75(2023), 393-424. Available at https://link.springer.com/article/10.1007/s10463-022-00849-z
- Sparse quantile regression via l_0-penalty. Discussion Papers #2023-03, Graduate School of Economics, Hitotsubashi University. Available at https://hdl.handle.net/10086/81451
[Editorial Services]
Annals of the Institute of Statistical Mathematics, Co-editor (2011-2015), Associate editor (2003-2011,2015-)
Japanese Journal of Statistics and Data Science, Coordinating editor (2023-2026)