Graduate School of Economics
HONDA Toshio
  • Curriculum Vitae
  • Research Results
  • Educational and Social Activities

日本語

Paper

1.Adaptively weighted group Lasso for semiparametric quantile regression models(jointly worked)
Bernoulli Vol.25,pp.3311-3338 2019 Academic journal
ISSN 1350-7265doiHERMES-IR
2.The de-biased group Lasso estimation for varying coefficient models
Forthcoming in Annals of the Institute of Statistical Mathematics (Discussion Paper #2018-04, Graduate School of Economics, Hitotsubashi University, 2019) 2019 Academic journal
ISSN 0020-3157HERMES-IR
3.Variable selection and structure identification for varying coefficient Cox models(jointly worked)
Journal of Multivariate Analysis Vol.161,pp.103-122 2017 Academic journal
ISSN 0047-259Xdoi
4.Efficient estimation in semivarying coefficient models for longitudinal/clustered data(jointly worked)
Annals of Statistics(http://imstat.org/aos/) Vol.44,No.5,pp.1988-2017 2016 Academic journal
ISSN 0090-5364Link
5.Forward variable selection for sparse ultra-high dimensional varying coefficient models(jointly worked)
Journal of the American Statistical Association Vol.111,pp.1209-1221 2016 Academic journal
ISSN 0162-1459doiHERMES-IR
6.Discussion on "Varying Coefficient Regression Models: A Review and New Developments by B.U.Park et al."
International Statistical Review Vol.83,pp.68-70 2015 Academic journal
ISSN 1751-5823doiLink
7.Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data(jointly worked)
Annals of Statistics Vol.42,pp.1819-1849 2014 Academic journal
ISSN 0090-5364Link
8.Variable selection in Cox regression models with varying coefficients(jointly worked)
Journal of Statistical Planning and Inference Vol.148,pp.67-81 2014 Academic journal
ISSN 0378-3758Link
9.Nonparametric LAD Cointegrating Regression
Journal of Multivariate Analysis Vol.117,pp.150-162 2013 Academic journal
ISSN 0047-259XHERMES-IR
10.Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors
Annals of the Institute of Statistical Mathematics Vol.65,pp.23-47 2013 Academic journal
ISSN 0020-3157HERMES-IR
11.Nonparametric estimation of conditional medians for linear and related processes
Annals of the Institute of Statistical Mathematics Vol.62,No.6,pp.995-1021 2010 Academic journal
ISSN 0020-3157doiHERMES-IR
12.Nonparametric regression for dependent data in the errors-in-variables problem
Journal of Statistical Planning and Inference Vol.140,pp.3409-3424 2010 Academic journal
ISSN 0378-3758doiHERMES-IR
13.Nonparametric density estimation for linear processes with infinite variance
Annals of the Institute of Statistical Mathematics Vol.61,No.2,pp.413-439 2009 Academic journal
ISSN 0020-3157doiHERMES-IR
14.A limit theorem for sums of bounded functional of linear processes without finite mean
Probability and Mathematical Statistics Vol.29,pp.337-351 2009 Academic journal
ISSN 0208-4147HERMES-IR
15.Estimation in Partial Linear Models under Long-Range Dependence
Discussion Papers #2007-07, Graduate School of Economics, Hitotsubashi University 2007 Bulletin of university, institute, etc.
HERMES-IR
16.Estimation in additive Cox models by marginal integration
Annals of the Institute of Statistical Mathematics Vol.57,No.3,pp.403-423 2005 Academic journal
ISSN 0020-3157doiHERMES-IR
17.Nonparametric regression in proportional hazards models
Journal of the Japan Statistical Society Vol.34,No.1,pp.1-17 2004 Academic journal
ISSN 0389-5602
18.Quantile regression in varying coefficient models
Journal of Statistical Planning and Inference Vol.121,No.1,pp.113-125 2004 Academic journal
ISSN 0378-3758
19.Nonparametric regression with current status data
Annals of the Institute of Statistical Mathematics Vol.56,No.1,pp.49-72 2004 Academic journal
ISSN 0020-3157
20.Nonparametric density estimation for a long-range dependent process
Annals of the Institute of Statistical Mathematics Vol.52,No.4,pp.599-611 2000 Academic journal
ISSN 0020-3157
21.Nonparametric estimation of the conditional median function for long-range dependent processes
Journal of the Japan Statistical Society Vol.30,No.2,pp.129-142 2000 Academic journal
ISSN 0389-5602Link
22.Nonparametric estimation of a conditional quantile for α-mixing processes
Annals of the Institute of Statistical Mathematics Vol.52,No.3,pp.459-470 2000 Academic journal
ISSN 0020-3157
23.Root-n-consistent semiparametric estimation of partially linear models for weakly dependent observations
Communications in Statistics-Theory and Methods Vol.28,No.8,pp.2001-2020 1999 Academic journal
ISSN 0361-0926
24.Testing the goodness of fit of a linear model by kernel regression
Communications in Statistics-Theory and Methods Vol.27,No.3,pp.529-546 1998 Academic journal
ISSN 0361-0926
25.Sequential Estimation of the Marginal Density Function for a Strongly Mixing Process
Sequential Analysis Vol.17,pp.239-251 1998 Academic journal
ISSN 0747-4946
26.The CUSUM tests with nonparametic regression residuals
Journal of the Japan Statistical Society Vol.27,No.1,pp.45-63 1997 Academic journal
ISSN 0389-5602Link
27.The effect of heteroscedasticity on the actual size of the Chow test(jointly worked)
Journal of the Japan Statistical Society Vol.26,No.2,pp.127-134 1996 Academic journal
ISSN 0389-5602Link
28.Estimating a covariance matrix of a normal distribution with unknown mean(jointly worked)
Journal of the Japan Statistical Society Vol.23,No.2,pp.131-144 1993 Academic journal
ISSN 0389-5602Link
29.Estimation of the mean by three stage procedures
Sequential Analysis Vol.11,pp.73-89 1992 Academic journal
ISSN 0747-4946
30.Construction of a confidence interval by triple sampling
Sequential Analysis Vol.11,pp.273-287 1992 Academic journal
ISSN 0747-4946
31.Minimax estimators in the MANOVA model for arbitrary quadratic loss and unkonwn covariance matrix
Journal of Multivariate Analysis Vol.36,pp.113-120 1991 Academic journal
ISSN 0047-259X

Oral Presentation

NOName of subject/Conference NameYearSite
1.The de-biased group Lasso estimation for varying coefficient models(DSSV2019)
2019.08Doshisha University, Japan
2.The de-biased group Lasso estimation for varying coefficient models(Statistical Mathematics Seminar)
2019.06The Institute of Statistical Mathematics, Japan
3.The de-biased group Lasso estimation for varying coefficient models(Seminar)
2019.03Institute of Statistics, National Tsing Hua University, Taiwan
4.The de-biased group Lasso estimation for varying coefficient models(Seminar)
2019.03Institute of Staistical Science, Academia Sinica, Taiwan
5.The de-biased group Lasso estimation for varying coefficient models(CMStatistics 2018)
2018.12University of Pisa, Italy
6.Adaptively weighted group Lasso for semiparametric quantile regression models(The 5th IMS-APRM Meeting)
2018.06National University of Singapore
7.Adaptively weighted group Lasso for semiparametric quantile regression models(CMStatistics 2017)
2017.12Senate House, University of London, UK
8.Variable selection and structure identification for varying coefficient Cox models(Seminar)
2017.08Institute of Statistics, National Tsing Hua University, Taiwan
9.Adaptively weighted group Lasso for semiparametric quantile regression models(European Meeting of Statisticians 2017)
2017.07University of Helsinki, Finland
10.* Variable selection and structure identification for varying coefficient Cox models(EcoSta 2017)
2017.06The Hong Kong University of Science and Technology
11.Adaptively weighted group Lasso for semiparametric quantile regression models(Seminar)
2017.06Department of Statistics, The Chinese University of Hong Kong
12.* Variable selection and structure identification for varying coefficient Cox models(CMStatistics 2016)
2016.12University of Seville, Seville, Spain
13.Variable selection and structure identification for varying coefficient Cox models(Statistical Mathematics Seminar)
2016.10The Institute of Statistical Mathematics, Japan
14.Variable selection and structure identification for varying coefficient Cox models(Mathematical statistics and stochastic analysis for modeling and analysis of complex random systemsⅢ)
2016.09Graduate School of Mathematical Sciences, The University of Tokyo
15.Variable selection and structure identification for varying coefficient Cox models(The Japanese Joint Statistical Meeting)
2016.09Kanazawa University, Japan
16.* Efficient estimation in semivarying coefficient models for longitudinal/clustered data(The 4th IMS-APRM Meeting)
2016.06The Chinese University of Hong Kong
17.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)
2016.05University of Tokyo
18.* Efficient estimation in semivarying coefficient models for longitudinal/clustered data(IASC-ARS 2015)
2015.12National University of Singapore
19.Efficient estimation in semivarying coefficient models for longitudinal/clustered data(Statistical Mathematics Seminar)
2015.11The Institute of Statistical Mathematics, Japan
20.* 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")
2015.11Waseda University
21.Efficient estimation in semivarying coefficient models for longitudinal/clustered data(Seminar)
2015.08Institute of Staistical Science, Academia Sinica, Taiwan
22.Efficient estimation in semivarying coefficient models for longitudinal/clustered data(European Meeting of Statisticians)
2015.07VU University Amsterdam, Amsterdam
23.Efficient estimation in semivarying coefficient models for longitudinal/clustered data(Waseda International Symposium "Asymptotic Sufficiency, Asymptotic Efficiency and Semimartingale")
2015.03Waseda University, Japan
24.Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data(Joint Satistical Meetings 2014)
2014.08Boston, Massachusetts
25.Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data(Waseda International Symposium on "Stable Process, Semimartingale, Finance & Pension Mathematics")
2014.03Waseda University, Japan
26.Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data(ERCIM 2013)
2013.12Senate House, University of London, UK
27.Variable selection in Cox regression models with varying coefficients(The 59th World Statistics Congress)
2013.08Hong Kong
28.Nonparametric quantile estimation for time series(Statistical Mathematics Seminar)
2013.05The Institute of Statistical Mathematics, Japan
29.Nonparametric quantile regression for time series(NCTS/TPE Statistics Seminar)
2013.02Dept. of Mathematics, National Taiwan University
30.Variable selection in Cox regression models with varying coefficients(ISI-ISM-ISSAS Joint Conference 2013)
2013.02Academia Sinica, Taipei
31.Variable selection in Cox regression models with varying coefficients(NCTS/TPE Statistics Seminar)
2012.07Dept. of Mathematics, National Taiwan University
32.Nonparametric LAD cointegrating regression(IMS-APRM2012)
2012.07Tsukuba, Japan
33.Variable selection in Cox regression models with varying coefficients(Economic Risk Seminar (CRC649, Humboldt-Universität zu Berlin))
2012.06Berlin, Germany
34.Nonparametric LAD cointegrating regression(Haindorf Seminar 2012 (Humboldt-Universität zu Berlin))
2012.02Hejnice, Czech Republic
35.Nonparametric LAD Cointegrating Regression(Recent Developments in Statistics, Empirical Finance and Econometrics)
2011.11Kyoto University, Japan
36.Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors(Joint Satistical Meetings 2011)
2011.08Miami Beach, Florida
37.Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors (poster presentation)(Graybill Conference 2011)
2011.06The Department of Statistics, Colorado State University
38.Estimation in Partial Linear Models under Long-Range Dependence (poster presentation) (The 2008 International Symposium on Econometric Theory and Applications )
2008.05Seoul National University
39.Noncentral Limit Theorems for Bounded Functions of Linear Processes without Finite Mean(The 2007 Japanese Joint Statistical Meeting)
2007.09Kobe University, Japan
40.Nonparametric Density Estimation for Linear Processes with Infinite Variance(Taipei International Statistics Workshop)
2006.12National Taiwan University, Taiwan
41.Nonparametric Density Estimation for Linear Processes with Infinite Variance(The 2006 Japanese Joint Statistical Meeting)
2006.09Tohoku University, Japan

Scientific Research Funds Results

NOResearch subjectResearch itemYear
1.
Scientific Research (C)2016-2018
2.
Scientific Research (C)2013-2015
3.
Scientific Research (A)2012-2015
4.
Scientific Research (A)2006-2009
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