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- HONDA Toshio
- Graduate School of Economics
- HONDA Toshio
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Books and Other Publications
| 1. | 『教養としての経済学』4-5-3分担執筆（一橋大学経済学部編）
本田 敏雄 (Contributor) 有斐閣 2013.2 (ISBN : 4641164045) |
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| 2. | 『計量経済学ハンドブック』第3章分担執筆（縄田和満，蓑谷千凰彦，和合肇編） （共著）
本田 敏雄 (Joint author) 朝倉書店 2007.4 (ISBN : 9784254290073) |
Papers
| 1. | Sparse quantile regression via l_0-penalty
Toshio Honda, Wei-Ying Wu Discussion Paper Series No. 2023-03, Graduate School of Economics, Hitotsubashi University 2024.11 
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| 2. | Forward variable selection for ultra-high dimensional quantile regression models (jointly worked) (Peer-reviewed) Toshio Honda, Chien-Tong Lin Annals of the Institute of Statistical Mathematics Vol.75,No.3,pp.393-424 2023.6 
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| 3. | Statistical inferences on high-dimensional Cox regression models(in Japanese) (Peer-reviewed) Toshio Honda Journal of the Japan Statistical Society(Japanese Issue) Vol.52,No.2,pp.113-129 2023.3
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| 4. | Forward Variable Selection for Sparse Ultra-High Dimensional Generalized Varying Coefficient Models (jointly worked) (Peer-reviewed) Toshio Honda, Chien-Tong LIN Japanese Journal of Statistics and Data Science Vol.4,pp.151-179 2021.7
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| 5. | The de-biased group Lasso estimation for varying coefficient models (Peer-reviewed) Toshio Honda Annals of the Institute of Statistical Mathematics Vol.73,pp.3-29 2021.2
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| 6. | Adaptively weighted group Lasso for semiparametric quantile regression models (jointly worked) (Peer-reviewed) Toshio Honda, Ching-Kang ING, Wei-Ying WU Bernoulli Vol.25,pp.3311-3338 2019.10
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| 7. | Variable selection and structure identification for varying coefficient Cox models (Peer-reviewed) Toshio Honda, Ryota Yabe JOURNAL OF MULTIVARIATE ANALYSIS Vol.161,pp.103-122 2017.9
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| 8. | EFFICIENT ESTIMATION IN SEMIVARYING COEFFICIENT MODELS FOR LONGITUDINAL/CLUSTERED DATA (Peer-reviewed) Ming-Yen Cheng, Toshio Honda, Jialiang Li ANNALS OF STATISTICS Vol.44,No.5,pp.1988-2017 2016.10
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| 9. | Forward Variable Selection for Sparse Ultra-High Dimensional Varying Coefficient Models (Peer-reviewed) Ming-Yen Cheng, Toshio Honda, Jin-Ting Zhang JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Vol.111,No.515,pp.1209-1221 2016.9
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| 10. | Discussion on "Varying Coefficient Regression Models: A Review and New Developments by B.U.Park et al."
Toshio Honda International Statistical Review Vol.83,No.1,pp.68-70 2015.4
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| 11. | Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data (jointly worked) (Peer-reviewed) Ming-Yen Cheng, Toshio Honda, Jialiang Li, Heng Peng Annals of Statistics Vol.42,pp.1819-1849 2014.8
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| 12. | Variable selection in Cox regression models with varying coefficients (Peer-reviewed) Toshio Honda, Wolfgang Karl Haerdle JOURNAL OF STATISTICAL PLANNING AND INFERENCE Vol.148,pp.67-81 2014.5
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| 13. | Nonparametric LAD Cointegrating Regression (Peer-reviewed) Toshio Honda Journal of Multivariate Analysis Vol.117,pp.150-162 2013.7
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| 14. | Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors (Peer-reviewed) Toshio Honda Annals of the Institute of Statistical Mathematics Vol.65,pp.23-47 2013.1
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| 15. | Nonparametric estimation of conditional medians for linear and related processes (Peer-reviewed) Toshio Honda ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Vol.62,No.6,pp.995-1021 2010.12
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| 16. | Nonparametric regression for dependent data in the errors-in-variables problem (Peer-reviewed) Toshio Honda JOURNAL OF STATISTICAL PLANNING AND INFERENCE Vol.140,No.11,pp.3409-3424 2010.11
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| 17. | Nonparametric density estimation for linear processes with infinite variance (Peer-reviewed) Toshio Honda ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Vol.61,No.2,pp.413-439 2009.6
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| 18. | A limit theorem for sums of bounded functional of linear processes without finite mean (Peer-reviewed) Toshio Honda Probability and Mathematical Statistics Vol.29,No.2,pp.337-351 2009.4
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| 19. | Estimation in Partial Linear Models under Long-Range Dependence
Toshio Honda Discussion Papers #2007-07, Graduate School of Economics, Hitotsubashi University 2007.7
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| 20. | Estimation in additive cox models by marginal integration (Peer-reviewed) T Honda ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Vol.57,No.3,pp.403-423 2005.9
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| 21. | Nonparametric regression in proportional hazards models (Peer-reviewed) Toshio Honda Journal of the Japan Statistical Society Vol.34,No.1,pp.1-17 2004.4 |
| 22. | Quantile regression in varying coefficient models (Peer-reviewed) T Honda JOURNAL OF STATISTICAL PLANNING AND INFERENCE Vol.121,No.1,pp.113-125 2004.3
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| 23. | Nonparametric regression with current status data (Peer-reviewed) T Honda ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Vol.56,No.1,pp.49-72 2004.3 |
| 24. | Nonparametric density estimation for a long-range dependent linear process (Peer-reviewed) T Honda ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Vol.52,No.4,pp.599-611 2000.12 |
| 25. | Nonparametric estimation of the conditional median function for long-range dependent processes (Peer-reviewed) Toshio Honda Journal of the Japan Statistical Society Vol.30,No.2,pp.129-142 2000.12
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| 26. | Nonparametric estimation of a conditional quantile for alpha-mixing processes (Peer-reviewed) T Honda ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS Vol.52,No.3,pp.459-470 2000.9 |
| 27. | Root-N-consistent semiparametric estimation of partially linear models for weakly dependent observations (Peer-reviewed) T Honda COMMUNICATIONS IN STATISTICS-THEORY AND METHODS Vol.28,No.8,pp.2001-2020 1999 |
| 28. | Sequential Estimation of the Marginal Density Function for a Strongly Mixing Process (Peer-reviewed) Toshio Honda Sequential Analysis Vol.17,pp.239-251 1998.4
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| 29. | Testing the goodness of fit of a linear model by kernel regression (Peer-reviewed) T Honda COMMUNICATIONS IN STATISTICS-THEORY AND METHODS Vol.27,No.3,pp.529-546 1998 |
| 30. | The CUSUM tests with nonparametic regression residuals (Peer-reviewed) Toshio Honda Journal of the Japan Statistical Society Vol.27,No.1,pp.45-63 1997.4
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| 31. | Exact distribution of an F-test statistic under misspecified error covariance matrices （共著）
Toshio Honda, Akimichi Takemura 大学院重点特別経費研究成果（筑波大学大学院社会科学研究科） pp.204-230 1997.3 |
| 32. | 非定常回帰モデルにおける構造変化の検定について
本田敏雄 経済学論集（筑波大学社会科学系経済学専攻） No.35,pp.1-16 1996.4 |
| 33. | The effect of heteroscedasticity on the actual size of the Chow test (jointly worked) (Peer-reviewed) Toshio Honda, Akimichi Takemura Journal of the Japan Statistical Society Vol.26,No.2,pp.127-134 1996.4
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| 34. | 非定常回帰モデルにおける構造変化の検定について（続）
本田敏雄 経済学論集（筑波大学社会科学系経済学専攻） No.36,pp.87-89 1996.4 |
| 35. | Testing Regression Coefficients When Error Terms Are Not Independently and Identically Distributed (Peer-reviewed) TAKEMURA Akimichi, HONDA Toshio The Journal of economics Vol.60,No.1,pp.28-50 1994.4
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| 36. | Estimating a covariance matrix of a normal distribution with unknown mean (jointly worked) (Peer-reviewed) Tatsuya Kubokawa, Toshio Honda, Kenji Morita, A. K. E. Saleh Journal of the Japan Statistical Society Vol.23,No.2,pp.131-144 1993.10
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| 37. | Construction of a confidence interval by triple sampling (Peer-reviewed) Toshio Honda Sequential Analysis Vol.11,pp.273-287 1992.4
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| 38. | Estimation of the mean by three stage procedures (Peer-reviewed) Toshio Honda Sequential Analysis Vol.11,pp.73-89 1992.4 |
| 39. | Minimax estimators in the manova model for arbitrary quadratic loss and unknown covariance matrix (Peer-reviewed) Toshio Honda Journal of Multivariate Analysis Vol.36,No.1,pp.113-120 1991
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Presentations
| No. | Name of subject/Conference Name | Year | Site |
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| 1. | Expected shortfall regression with high-dimensional covariates(Fertile Field of Mathematical Statistics (Grant-in-Aid for Scientific Research Research Conference)) |
Holding date :
2024.12.21 Presentation date : 2024.12.21 |
Graduate School of Economics, University of Tokyo |
| 2. | Expected shortfall regression with high-dimensional covariates(SDS Workshop on Financial Theory and Econometrics) |
Holding date :
2024.11.5 Presentation date : 2024.11.5 |
SDS, Hitotsubashi University |
| 3. | Sparse quantile regression via l_0 penalty(統計科学・機械学習・情報数学の最前線（科研費シンポジウム）) |
Holding date :
2024.1.26
- 2024.1.27 Presentation date : 2024.1.27 |
東北大学大学院情報科学研究科 |
| 4. | Forward variable selection for ultra-high dimensional models(EcoSta2023) |
Holding date :
2023.8.1
- 2023.8.3 Presentation date : 2023.8.2 |
Waseda University, Tokyo |
| 5. | Statistical Inferences on high-dimensional Cox regression models(2022年度統計関連学会連合大会) |
Holding date :
Presentation date : 2022.9.6 |
成蹊大学 |
| 6. | Forward variable selection for ultra-high dimensional quantile regression models(Waseda International Symposium Topological Data Science, Causality, Analysis of Variance & Time Series) |
Holding date :
Presentation date : 2022.3.9 |
Waseda University (Hybrid) |
| 7. | Forward variable selection for ultra-high dimensional quantile regression models(IASC-ARS 2022) |
Holding date :
Presentation date : 2022.2.23 |
Doshisha University (hybrid) |
| 8. | Forward variable selection for ultra-high dimensional quantile regression models(科研費研究集会「データサイエンス・統計学における方法論と応用の新展開」) |
Holding date :
Presentation date : 2021.12.3 |
長崎大学情報科学部（オンライン開催） |
| 9. | Forward Variable Selection for Sparse Ultra-High Dimensional Generalized Varying Coefficient Models(科研費研究集会『多様な分野のデータに対する統計科学・機械学習的アプロー チ』) |
Holding date :
Presentation date : 2020.9.28 |
滋賀大学データサイエンス学部（オンライン開催） |
| 10. | 高次元データ解析と前進型変数選択法(統計数理研究所リスク解析戦略研究センターシンポジウム) |
Holding date :
Presentation date : 2020.8.31 |
統計数理研究所（オンライン開催） |
| 11. | The de-biased group Lasso estimation for varying coefficient models(科研費研究集会「多様な高次元モデルにおける理論と方法論，及び，関連分野への応用」) |
Holding date :
Presentation date : 2020.2.1 |
イーアスつくば，茨城県 |
| 12. | The de-biased group Lasso estimation for varying coefficient models(関西計量経済学研究会) |
Holding date :
Presentation date : 2020.1.11 |
一橋大学 |
| 13. | The de-biased group Lasso estimation for varying coefficient models(DSSV2019) |
Holding date :
Presentation date : 2019.8.13 |
同志社大学 |
| 14. | The de-biased group Lasso estimation for varying coefficient models(Statistical Mathematics Seminar) |
Holding date :
Presentation date : 2019.6.12 |
統計数理研究所 |
| 15. | The de-biased group Lasso estimation for varying coefficient models(Seminar, Institute of Staistical Science, Academia Sinica) |
Holding date :
Presentation date : 2019.3.25 |
Institute of Statistics, National Tsing Hua University, Taiwan |
| 16. | The de-biased group Lasso estimation for varying coefficient models(Seminar, Institute of Statistics, National Tsing Hua University) |
Holding date :
Presentation date : 2019.3.21 |
Institute of Staistical Science, Academia Sinica, Taiwan |
| 17. | The de-biased group Lasso estimation for varying coefficient models(CMStatistics 2018) |
Holding date :
Presentation date : 2018.12.14 |
University of Pisa, Italy |
| 18. | Adaptively weighted group Lasso for semiparametric quantile regression models(The 5th IMS-APRM Meeting) |
Holding date :
Presentation date : 2018.6.26 |
National University of Singapore |
| 19. | Adaptively weighted group Lasso for semiparametric quantile regression models(CMStatistics 2017) |
Holding date :
Presentation date : 2017.12.16 |
Senate House, University of London, UK |
| 20. | Variable selection and structure identification for varying coefficient Cox models(Seminar, Institute of Statistics, National Tsing Hua University) |
Holding date :
Presentation date : 2017.8.22 |
Institute of Statistics, National Tsing Hua University, Taiwan |
| 21. | Adaptively weighted group Lasso for semiparametric quantile regression models(European Meeting of Statisticians 2017) |
Holding date :
Presentation date : 2017.7.24 |
University of Helsinki, Finland |
| 22. | Adaptively weighted group Lasso for semiparametric quantile regression models(Seminar, Department of Statistics, The Chinese University of Hong Kong) |
Holding date :
Presentation date : 2017.6.15 |
Department of Statistics, The Chinese University of Hong Kong |
| 23. | Variable selection and structure identification for varying coefficient Cox models(EcoSta 2017) |
Holding date :
Presentation date : 2017.6.15 |
The Hong Kong University of Science and Technology |
| 24. | Variable selection and structure identification for varying coefficient Cox models(CMStatistics 2016) |
Holding date :
Presentation date : 2016.12.9 |
University of Seville, Seville, Spain |
| 25. | Variable selection and structure identification for varying coefficient Cox models(科研費研究集会『応用統計学のひろがり』) |
Holding date :
Presentation date : 2016.10.29 |
統計数理研究所 |
| 26. | Variable selection and structure identification for varying coefficient Cox models(Statistical Mathematics Seminar) |
Holding date :
Presentation date : 2016.10.19 |
統計数理研究所 |
| 27. | Variable selection and structure identification for varying coefficient Cox models(Mathematical statistics and stochastic analysis for modeling and analysis of complex random systemsⅢ) |
Holding date :
Presentation date : 2016.9.27 |
東京大学大学院数理科学研究科 |
| 28. | Variable selection and structure identification for varying coefficient Cox models(The Japanese Joint Statistical Meeting) |
Holding date :
Presentation date : 2016.9.4 |
Kanazawa University, Japan |
| 29. | Efficient estimation in semivarying coefficient models for longitudinal/clustered data(The 4th IMS-APRM Meeting) |
Holding date :
Presentation date : 2016.6.27 |
香港中文大学 |
| 30. | Forward variable selection for sparse ultra-high dimensional varying coefficient models and Efficient estimation in semivarying coefficient models for longitudinal/clustered data(Applied Statistics Workshop, The University of Tokyo) |
Holding date :
Presentation date : 2016.5.6 |
University of Tokyo |
| 31. | Efficient estimation in semivarying coefficient models for longitudinal/clustered data(IASC-ARS 2015) |
Holding date :
Presentation date : 2015.12.17 |
National University of Singapore |
| 32. | Efficient estimation in semivarying coefficient models for longitudinal/clustered data(Statistical Mathematics Seminar) |
Holding date :
Presentation date : 2015.11.25 |
統計数理研究所 |
| 33. | Forward variable selection for sparse ultra-high dimensional varying coefficient Models(Waseda International Symposium "High Dimensional Statistical Analysis for Spatio-Temporal Processes & Quantile Analysis for Time Series") |
Holding date :
Presentation date : 2015.11.9 |
早稲田大学 |
| 34. | Efficient estimation in semivarying coefficient models for longitudinal/clustered data(Seminar, Institute of Staistical Science, Academia Sinica) |
Holding date :
Presentation date : 2015.8.24 |
Institute of Staistical Science, Academia Sinica, Taiwan |
| 35. | Efficient estimation in semivarying coefficient models for longitudinal/clustered data(European Meeting of Statisticians) |
Holding date :
Presentation date : 2015.7.7 |
VU University Amsterdam, Amsterdam |
| 36. | Efficient estimation in semivarying coefficient models for longitudinal/clustered data(Waseda International Symposium "Asymptotic Sufficiency, Asymptotic Efficiency and Semimartingale") |
Holding date :
Presentation date : 2015.3.2 |
早稲田大学 |
| 37. | Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data(Joint Satistical Meetings 2014) |
Holding date :
Presentation date : 2014.8.2 |
Boston, Massachusetts |
| 38. | Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data(Waseda International Symposium on "Stable Process, Semimartingale, Finance & Pension Mathematics") |
Holding date :
Presentation date : 2014.3.3 |
早稲田大学 |
| 39. | Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data(ERCIM 2013) |
Holding date :
Presentation date : 2013.12.14 |
Senate House, University of London, UK |
| 40. | Variable selection in Cox regression models with varying coefficients(The 59th World Statistics Congress) |
Holding date :
Presentation date : 2013.8.25 |
Hong Kong |
| 41. | Nonparametric quantile regression for time series(Seminar, Department of Mathematics, Hong Kong Baptist University) |
Holding date :
Presentation date : 2013.8.20 |
Hong Kong |
| 42. | Nonparametric quantile estimation for time series(Statistical Mathematics Seminar) |
Holding date :
Presentation date : 2013.5.22 |
The Institute of Statistical Mathematics, Japan |
| 43. | Nonparametric quantile regression for time series(NCTS/TPE Statistics Seminar, National Taiwan University) |
Holding date :
Presentation date : 2013.2.5 |
Dept. of Mathematics, National Taiwan University |
| 44. | Variable selection in Cox regression models with varying coefficients(ISI-ISM-ISSAS Joint Conference 2013) |
Holding date :
Presentation date : 2013.2.1 |
Academia Sinica, Taipei |
| 45. | Nonparametric quantile estimation for time series(関西計量経済学研究会) |
Holding date :
Presentation date : 2013.1.12 |
一橋大学佐野書院 |
| 46. | Variable selection in Cox regression models with varying coefficients(研究集会 数理統計学の沃野) |
Holding date :
Presentation date : 2012.11.1 |
慶應義塾大学理工学部 |
| 47. | Variable selection in Cox regression models with varying coefficients(NCTS/TPE Statistics Seminar, National Taiwan University) |
Holding date :
Presentation date : 2012.7.25 |
Dept. of Mathematics, National Taiwan University |
| 48. | Nonparametric LAD cointegrating regression(IMS-APRM2012) |
Holding date :
Presentation date : 2012.7.3 |
Tsukuba, Japan |
| 49. | Variable selection in Cox regression models with varying coefficients(Economic Risk Seminar (CRC649, Humboldt-Universität zu Berlin)) |
Holding date :
Presentation date : 2012.6.25 |
Berlin, Germany |
| 50. | Nonparametric LAD cointegrating regression(Haindorf Seminar 2012 (Humboldt-Universität zu Berlin)) |
Holding date :
Presentation date : 2012.2.9 |
Hejnice, Czech Republic |
| 51. | Nonparametric LAD Cointegrating Regression(Recent Developments in Statistics, Empirical Finance and Econometrics) |
Holding date :
Presentation date : 2011.11.29 |
京都大学 |
| 52. | Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors(Joint Satistical Meetings 2011) |
Holding date :
Presentation date : 2011.8.1 |
Miami Beach, Florida |
| 53. | Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors (poster presentation)(Graybill Conference 2011) |
Holding date :
Presentation date : 2011.6.22 |
The Department of Statistics, Colorado State University |
| 54. | 線形過程における密度関数と回帰関数のノンパラメトリックス推定について(日本数学会2010年度年会統計数学分科会特別講演) |
Holding date :
Presentation date : 2010.3.24 |
慶應義塾大学 |
| 55. | Estimation in Partial Linear Models under Long-Range Dependence (poster presentation)(The 2008 International Symposium on Econometric Theory and Applications) |
Holding date :
Presentation date : 2008.5.1 |
Seoul National University |
| 56. | Noncentral Limit Theorems for Bounded Functions of Linear Processes without Finite Mean(The 2007 Japanese Joint Statistical Meeting) |
Holding date :
Presentation date : 2007.9.6 |
Kobe University, Japan |
| 57. | Nonparametric Density Estimation for Linear Processes with Infinite Variance(Taipei International Statistics Workshop) |
Holding date :
Presentation date : 2006.12.1 |
National Taiwan University, Taiwan |
| 58. | Nonparametric Density Estimation for Linear Processes with Infinite Variance(The 2006 Japanese Joint Statistical Meeting) |
Holding date :
Presentation date : 2006.9.1 |
Tohoku University, Japan |
Awards
| No. | Award name | Year |
|---|---|---|
| 1. | Research Achievement Award | 2022.5 |
| 2. | 統計学研究奨励小川基金会賞 | 1998.10 |
Research Projects
| No. | Research subject | Research item(Awarding organization, System name) | Year |
|---|---|---|---|
| 1. | Studies on structured nonparametric regression models for ultra-high dimensional data
|
Grant-in-Aid for Scientific Research (C)
( Awarding organization: Japan Society for the Promotion of Science System name: Grants-in-Aid for Scientific Research ) |
2024.4 - 2027.3 |
| 2. | Studies on statistical inference for ultra-high dimensional semiparametric models
|
Grant-in-Aid for Scientific Research (C)
( Awarding organization: Japan Society for the Promotion of Science System name: Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C) ) |
2020.4 - 2023.3 |
| 3. | 超高次元データに対する説明変数のスクリーニング手法に関する研究(研究代表者)
|
基盤研究(C)
( Awarding organization: 日本学術振興会 System name: 科学研究費助成事業 ) |
2016.4 - 2019.3 |
| 4. | 高次元変動係数モデルにおける変数選択に関する研究（研究代表者）
|
基盤研究(C)
( Awarding organization: 日本学術振興会 System name: 科学研究費助成事業 ) |
2013.4 - 2016.3 |
| 5. | 金融工学からERMへ：基礎理論と実証に関する研究（研究分担者）
|
基盤研究(A)
( Awarding organization: 日本学術振興会 System name: 科学研究費助成事業 ) |
2012.4 - 2016.3 |
| 6. | Studies on high-dimensional data
|
2012.4 | |
| 7. | 計算代数統計学の展開（研究分担者）
|
基盤研究(A)
( Awarding organization: 日本学術振興会 System name: 科学研究費助成事業 ) |
2006.4 - 2010.3 |
| 8. | Studies on Survival Analysis
|
2002.4 | |
| 9. | Studies on nonparametric and semiparametric regression
|
1997.4 |
