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Researches on the applicability of shrinkage estimation methods and related procedures

Research Project

Project/Area Number 18K01546
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 07030:Economic statistics-related
Research InstitutionKobe University

Principal Investigator

Namba Akio  神戸大学, 経済学研究科, 教授 (60324901)

Project Period (FY) 2018-04-01 – 2023-03-31
Project Status Completed (Fiscal Year 2022)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2022: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2021: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2020: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywords縮小推定量 / リサンプリング法 / ブートストラップ法 / 縮小推定 / ブートストラップ / リサンプリング / スタイン型分散推定量 / スタイン型推定料 / 漸近分布
Outline of Final Research Achievements

The main purpose of this research is to investigate the availability of shrinkage estimators. Through this research, it became clear that the shrinkage estimators are useful in various situations such as the model with proxy explanatory variables, and the model with a possible structural break. Also, the problem concerned with the application of the shrinkage estimators is that the distributions are complex and dependent on unknown parameters. However, it is proved that the approximations of the distributions of the shrinkage estimators are valid if we use the resampling methods such as m out of n bootstrap or bootstrap which incorporates the pretest.

Academic Significance and Societal Importance of the Research Achievements

縮小推定量が、その優れた特性にも関わらず、実際の応用であまり利用されていない理由の一つとして、推定量の分布が複雑であることが挙げられる。しかしながら、機械学習等で用いられる近代的な手法が、縮小推定法の一種として解釈できることが明らかになってきた。このため、実際のモデル・データへの応用において縮小推定法の重要性が近年再認識され、新たな研究テーマが多数生み出されている。本研究で得られた成果は、縮小推定量の分布の近似法を提案したこと、及び様々な状況下での縮小推定量の有効性を示しており、推定量の応用可能性を広げたものとして学術的意義がある。

Report

(6 results)
  • 2022 Annual Research Report   Final Research Report ( PDF )
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (8 results)

All 2021 2020 2018 Other

All Int'l Joint Research (3 results) Journal Article (5 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 3 results)

  • [Int'l Joint Research] Xiamen University(中国)

    • Related Report
      2022 Annual Research Report
  • [Int'l Joint Research] Xiamen University(中国)

    • Related Report
      2018 Research-status Report
  • [Int'l Joint Research] University of California-Riverside(米国)

    • Related Report
      2018 Research-status Report
  • [Journal Article] Bootstrapping the Stein-Rule Estimators2021

    • Author(s)
      Namba Akio
    • Journal Title

      Journal of Quantitative Economics

      Volume: 19 Issue: S1 Pages: 219-237

    • DOI

      10.1007/s40953-021-00269-5

    • Related Report
      2021 Research-status Report
    • Peer Reviewed
  • [Journal Article] スタイン分散推定量へのブートストラップ法の応用に関する一考察2021

    • Author(s)
      難波明生
    • Journal Title

      国民経済雑誌

      Volume: 224 Pages: 33-44

    • NAID

      40022693976

    • Related Report
      2021 Research-status Report
  • [Journal Article] Bootstrapping the Stein-Rule Estimators2021

    • Author(s)
      Akio Namba
    • Journal Title

      Journal of Quantitative Economics

      Volume: -

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] 漸近分布およびブートストラップ法によるスタイン型推定量の分布近似に関するシミュレーション分析2020

    • Author(s)
      難波明生
    • Journal Title

      国民経済雑誌

      Volume: 221 Pages: 73-84

    • NAID

      120006975844

    • Related Report
      2019 Research-status Report
  • [Journal Article] PMSE dominance of the positive-part shrinkage estimator in a regression model with proxy variables2018

    • Author(s)
      Akio Namba & Haifeng Xu
    • Journal Title

      Journal of Statistical Computation and Simulation

      Volume: 88:15 Issue: 15 Pages: 2893-2908

    • DOI

      10.1080/00949655.2018.1491576

    • Related Report
      2018 Research-status Report
    • Peer Reviewed / Int'l Joint Research

URL: 

Published: 2018-04-23   Modified: 2024-01-30  

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