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Research on variable selection for high-dimensional varying coefficient models

Research Project

Project/Area Number 25400197
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Foundations of mathematics/Applied mathematics
Research InstitutionHitotsubashi University

Principal Investigator

HONDA Toshio  一橋大学, 大学院経済学研究科, 教授 (30261754)

Project Period (FY) 2013-04-01 – 2016-03-31
Project Status Completed (Fiscal Year 2015)
Budget Amount *help
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Keywords変数選択 / 高次元データ / 変動係数モデル / セミパラメトリックモデル / longitudinal data
Outline of Final Research Achievements

I considered variable selection for high-dimensional varying coefficient models for longitudinal data and obtained some significant results. Specifically, I proposed with collaborators a useful two-step procedure to identify the true semi-varying coefficient model of the longitudinal data. The procedure consists of the nonparametric independence screening and the group SCAD method. Besides, I proposed an efficient estimator of the constant coefficients of the true semi-varying coefficient. I proved its desirable theoretical properties and some numerical properties were also investigated in our collaborative papers. In addition, I also obtained some theoretical results for a forward variable selection procedure for high-dimensional variable coefficient models and Cox models with variable coefficients. Numerical properties were also examined in our collaborative papers.

Report

(4 results)
  • 2015 Annual Research Report   Final Research Report ( PDF )
  • 2014 Research-status Report
  • 2013 Research-status Report
  • Research Products

    (16 results)

All 2016 2015 2014 2013 Other

All Int'l Joint Research (3 results) Journal Article (4 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 4 results,  Acknowledgement Compliant: 3 results) Presentation (8 results) (of which Int'l Joint Research: 3 results,  Invited: 2 results) Remarks (1 results)

  • [Int'l Joint Research] National Taiwan University(Taiwan)

    • Related Report
      2015 Annual Research Report
  • [Int'l Joint Research] National University of Singapore(Singapore)

    • Related Report
      2015 Annual Research Report
  • [Int'l Joint Research] Humboldt University of Berlin(Germany)

    • Related Report
      2015 Annual Research Report
  • [Journal Article] Efficient estimation in semivarying coefficient models for longitudinal/clustered data2016

    • Author(s)
      Ming-Yen Cheng, Toshio Honda, Jialiang Li
    • Journal Title

      The Annals of Statistics

      Volume: 印刷中

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Forward variable selection for sparse ultra-high dimensional varying coefficient models2016

    • Author(s)
      Ming-Yen Cheng, Toshio Honda and Jin-Ting Zhang
    • Journal Title

      Journal of the American Statistical Association

      Volume: 印刷中 Issue: 515 Pages: 1209-1221

    • DOI

      10.1080/01621459.2015.1080708

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Nonparametric independence screening and structure identification for ultra-high dimensional longitudinal data2014

    • Author(s)
      Ming-Yen Cheng, Toshio Honda, Jialiang Li, Heng Peng
    • Journal Title

      Annals of Statistics

      Volume: 42 Issue: 5 Pages: 1819-1849

    • DOI

      10.1214/14-aos1236

    • Related Report
      2014 Research-status Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] Variable selection in Cox regression models with varying coefficients2014

    • Author(s)
      Toshio Honda, Wolfgang Karl Hardle
    • Journal Title

      Journal of Statistical Planning and Inference

      Volume: 148 Pages: 67-81

    • DOI

      10.1016/j.jspi.2013.12.002

    • Related Report
      2013 Research-status Report
    • Peer Reviewed
  • [Presentation] Efficient estimation in semivarying coefficient models for longitudinal/clustered data2015

    • Author(s)
      Ming-Yen Cheng, Toshio Honda, Jialiang Li
    • Organizer
      IASC-ARS 2015
    • Place of Presentation
      Singapore (Singapore)
    • Year and Date
      2015-12-18
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Forward variable selection for sparse ultra-high dimensional varying coefficient models2015

    • Author(s)
      Ming-Yen Cheng, Toshio Honda, Jin-Ting Zhang
    • Organizer
      Waseda International Symposium "High Dimensional Statistical Analysis for Spatio-Temporal Processes & Quantile Analysis for Time Series"
    • Place of Presentation
      Waseda University (Tokyo, Shinjuku-ku)
    • Year and Date
      2015-11-11
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Efficient estimation in semivarying coefficient models for longitudinal/clustered data2015

    • Author(s)
      Toshio Honda, Ming-Yen Cheng, Jialiang Li
    • Organizer
      European Meeting of Statisticians
    • Place of Presentation
      Amsterdam (The Netherlands)
    • Year and Date
      2015-07-07
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Efficient estimation in semivarying coefficient models for longitudinal/clustered data2015

    • Author(s)
      Toshio Honda
    • Organizer
      Waseda International Symposium "Asymptotic Sufficiency, Asymptotic Efficiency and Semimartingale"
    • Place of Presentation
      早稲田大学理工学部、東京
    • Year and Date
      2015-03-03
    • Related Report
      2014 Research-status Report
  • [Presentation] Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data2014

    • Author(s)
      Toshio Honda
    • Organizer
      Joint Statistical Meetings 2014
    • Place of Presentation
      Boston Convention and Exhibition Center, Boston, US
    • Year and Date
      2014-08-06
    • Related Report
      2014 Research-status Report
  • [Presentation] Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal dat2014

    • Author(s)
      Toshio Honda
    • Organizer
      Stable Process, Semimartingale, Finance & Pension Mathematics
    • Place of Presentation
      早稲田大学理工キャンパス, 東京
    • Related Report
      2013 Research-status Report
  • [Presentation] Variable selection in Cox regression models with varying coefficients2013

    • Author(s)
      Toshio Honda
    • Organizer
      The 59th World Statistics Congress
    • Place of Presentation
      Hong Kong Convention and Exhibition Centre, Hong Kong, China
    • Related Report
      2013 Research-status Report
  • [Presentation] Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal dat2013

    • Author(s)
      Toshio Honda
    • Organizer
      ERCIM 2013
    • Place of Presentation
      Senate House, Univeristy of London, UK
    • Related Report
      2013 Research-status Report
  • [Remarks] 一橋大学大学院経済学研究科教員紹介

    • URL

      http://www.econ.hit-u.ac.jp/~koho/jpn/introduce/professor/ST_honda.html

    • Related Report
      2013 Research-status Report

URL: 

Published: 2014-07-25   Modified: 2022-02-01  

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