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Uematsu Yoshimasa  植松 良公

… Alternative Names

UEMATSU Yoshimasa  植松 良公

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Researcher Number 40835279
Other IDs
  • ORCIDhttps://orcid.org/0000-0002-0983-3143
Affiliation (Current) 2025: 一橋大学, 大学院ソーシャル・データサイエンス研究科, 准教授
Affiliation (based on the past Project Information) *help 2023 – 2025: 一橋大学, 大学院ソーシャル・データサイエンス研究科, 准教授
2020 – 2023: 一橋大学, ソーシャル・データサイエンス教育研究推進センター, 准教授
2019 – 2021: 東北大学, 経済学研究科, 准教授
Review Section/Research Field
Principal Investigator
Basic Section 07030:Economic statistics-related / Sections That Are Subject to Joint Review: Basic Section07030:Economic statistics-related , Basic Section07060:Money and finance-related / Basic Section 07060:Money and finance-related
Except Principal Investigator
Basic Section 07030:Economic statistics-related / Sections That Are Subject to Joint Review: Basic Section60030:Statistical science-related , Basic Section61030:Intelligent informatics-related / Basic Section 61030:Intelligent informatics-related / Basic Section 60030:Statistical science-related
Keywords
Principal Investigator
ファクター / 高次元時系列 / FDRコントロール / 統計的推測 / ノックオフ / バイアス修正 / ベクトル自己回帰 / 検出力 / ポートフォリオ選択 / 分散共分散行列 … More / 高次元データ / スパース性 / 偽発見率 / 高次元統計学 / ベクトル自己回帰モデル / ファクターモデル … More
Except Principal Investigator
統計的推測 / 高次元データ / ポートフォリオ選択 / 統計的推定・推論 / 深層モデル / 非スパースモデル / 高次元統計学 / 大規模モデル / Multiple testing / Weak factors / 罰則項付縮小ランク回帰 / 共トレンド推定 / Asset pricing / 景気循環成分 / ホドリック・プレスコット・フィルター / トレンド / 罰則化法 / ファクターモデル / 時系列データ / パネルデータ / climate change / co2 emission / energy consumption / inflation / factor model / panel data Less
  • Research Projects

    (6 results)
  • Research Products

    (22 results)
  • Co-Researchers

    (9 People)
  •  社会科学の発展に向けた「探索的データ分析」の方法論の開発Principal Investigator

    • Principal Investigator
      植松 良公
    • Project Period (FY)
      2025 – 2027
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 07030:Economic statistics-related
      Basic Section 07060:Money and finance-related
      Sections That Are Subject to Joint Review: Basic Section07030:Economic statistics-related , Basic Section07060:Money and finance-related
    • Research Institution
      Hitotsubashi University
  •  Theoretical development of non-sparse high-dimensional statistics for statistical understanding and utilization of large-degree-of-freedom models

    • Principal Investigator
      今泉 允聡
    • Project Period (FY)
      2024 – 2026
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 60030:Statistical science-related
      Basic Section 61030:Intelligent informatics-related
      Sections That Are Subject to Joint Review: Basic Section60030:Statistical science-related , Basic Section61030:Intelligent informatics-related
    • Research Institution
      The University of Tokyo
  •  Portfolio Selection for High-Dimensional Data

    • Principal Investigator
      田中 晋矢
    • Project Period (FY)
      2024 – 2026
    • Research Category
      Grant-in-Aid for Scientific Research (C)
    • Review Section
      Basic Section 07030:Economic statistics-related
    • Research Institution
      Otaru University of Commerce
  •  反実仮想実験による炭素価格付加政策の排出削減効果と世界経済への影響の分析

    • Principal Investigator
      山形 孝志
    • Project Period (FY)
      2021 – 2023
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 07030:Economic statistics-related
    • Research Institution
      Osaka University
  •  Econometric analysis of time series and panel data using factor models and penalization methods: theory and applications

    • Principal Investigator
      Hayakawa Kazuhiko
    • Project Period (FY)
      2020 – 2022
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 07030:Economic statistics-related
    • Research Institution
      Hiroshima University
  •  Construction of the global inference theory in high-dimensional macroeconometricsPrincipal Investigator

    • Principal Investigator
      UEMATSU Yoshimasa
    • Project Period (FY)
      2019 – 2023
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 07030:Economic statistics-related
    • Research Institution
      Hitotsubashi University
      Tohoku University

All 2023 2022 2021 2020 2019

All Journal Article Presentation Book

  • [Book] 経済経営のデータサイエンス2022

    • Author(s)
      石垣 司、植松 良公、千木良 弘朗、照井 伸彦、松田 安昌、李 銀星
    • Total Pages
      248
    • Publisher
      共立出版
    • ISBN
      9784320125193
    • Data Source
      KAKENHI-PROJECT-20H01484
  • [Journal Article] Estimation of large covariance matrices with mixed factor structures2023

    • Author(s)
      Runyu Dai, Yoshimasa Uematsu, Yasumasa Matsuda
    • Journal Title

      The Econometrics Journal

      Volume: 27 Issue: 1 Pages: 62-83

    • DOI

      10.1093/ectj/utad018

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-19K13665, KAKENHI-PROJECT-20H01484
  • [Journal Article] Discovering the Network Granger Causality in Large Vector Autoregressive Models2023

    • Author(s)
      Yoshimasa Uematsu,Takashi Yamagata
    • Journal Title

      arXiv

      Volume: arXiv:2303.15158

    • Open Access
    • Data Source
      KAKENHI-PROJECT-21H00700
  • [Journal Article] Estimation of Sparsity-Induced Weak Factor Models2022

    • Author(s)
      Uematsu Yoshimasa、Yamagata Takashi
    • Journal Title

      Journal of Business & Economic Statistics

      Volume: Forthcoming Issue: 1 Pages: 1-15

    • DOI

      10.1080/07350015.2021.2008405

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K01545, KAKENHI-PROJECT-19K13665, KAKENHI-PROJECT-21H04397, KAKENHI-PROJECT-20H01484, KAKENHI-PROJECT-20H05631, KAKENHI-PROJECT-21H00700
  • [Journal Article] Inference in Sparsity-Induced Weak Factor Models2021

    • Author(s)
      Uematsu Yoshimasa、Yamagata Takashi
    • Journal Title

      Journal of Business & Economic Statistics

      Volume: Forthcoming Issue: 1 Pages: 1-14

    • DOI

      10.1080/07350015.2021.2003203

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K01545, KAKENHI-PROJECT-19K13665, KAKENHI-PROJECT-21H04397, KAKENHI-PROJECT-20H01484, KAKENHI-PROJECT-21H00700
  • [Journal Article] IPAD: stable interpretable forecasting with knockoffs inference2019

    • Author(s)
      Yingying Fan, Jinchi Lv, Mahrad Sharifvaghefi, Yoshimasa Uematsu
    • Journal Title

      Journal of the American Statistical Association

      Volume: - Issue: 532 Pages: 1822-1834

    • DOI

      10.1080/01621459.2019.1654878

    • NAID

      120006557977

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Journal Article] High‐dimensional macroeconomic forecasting and variable selection via penalized regression2019

    • Author(s)
      Uematsu Yoshimasa and Tanaka Shinya
    • Journal Title

      The Econometrics Journal

      Volume: 22 Issue: 1 Pages: 34-56

    • DOI

      10.1111/ectj.12117

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-16K17100, KAKENHI-PROJECT-19K13665
  • [Journal Article] SOFAR: large-scale association network learning2019

    • Author(s)
      Yoshimasa Uematsu, Yingying Fan, Kun Chen, Jinchi Lv, Wei Lin
    • Journal Title

      IEEE Transactions on Information Theory

      Volume: 65 Issue: 8 Pages: 4924-4939

    • DOI

      10.1109/tit.2019.2909889

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] Revisiting asymptotic theory for principal component estimators of approximate factor models2023

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      16th CMStatistics 2023, Berlin, Germany
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] High-dimensional robust inference via the debiased rank lasso2022

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      5th International Conference on Econometrics and Statistics (EcoSta 2022)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21H00700
  • [Presentation] High-dimensional asymptotics for single-index models via approximate message passing2022

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      15th CMStatistics 2022
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21H00700
  • [Presentation] High-dimensional robust inference via the debiased rank lasso2022

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      5th International Conference on Econometrics and Statistics (EcoSta 2022)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] High-dimensional asymptotics for single-index models via approximate message passing2022

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      15th CMStatistics 2022
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] 高次元データにおける統計的推測とその高次元ベクトル自己回帰への応用2021

    • Author(s)
      植松良公
    • Organizer
      統計関連学会連合大会
    • Invited
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] On weak factor models2021

    • Author(s)
      植松良公
    • Organizer
      日本統計学会春季集会
    • Invited
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] On weak factor models2021

    • Author(s)
      植松良公
    • Organizer
      関西計量経済学研究会
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] Robust False Discovery Rate Control via Debiased Rank Lasso2021

    • Author(s)
      植松良公
    • Organizer
      Applications of Data Science in Social Science
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] Inference in weak factor models2020

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      Econometric Society World Congress 2020
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] IPAD: stable interpretable forecasting with knockoffs inference2019

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      11th CSA-KSS-JSS Joint International Session
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] Estimation of weak factor models2019

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      39th International Symposium on Forecasting
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] IPAD: stable interpretable forecasting with knockoffs inference2019

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      11th ICSA International Conference
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • [Presentation] Large-dimensional vector autoregression2019

    • Author(s)
      Yoshimasa Uematsu
    • Organizer
      2019 UEA-Tohoku Joint Workshop
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K13665
  • 1.  山形 孝志 (20813231)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 3 results
  • 2.  Hayakawa Kazuhiko (00508161)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 3.  敦賀 貴之 (40511720)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 4.  生藤 昌子 (60452380)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 5.  山田 宏 (90292078)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 6.  今泉 允聡 (90814088)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 7.  仲北 祥悟 (80855114)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 8.  矢田 和善 (90585803)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 9.  田中 晋矢 (80727149)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 1 results

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