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2010 Fiscal Year Final Research Report

Theory of Bayesian Multiscale Bootstrap and its Applications

Research Project

  • PDF
Project/Area Number 20500254
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Statistical science
Research InstitutionTokyo Institute of Technology

Principal Investigator

SHIMODAIRA Hidetoshi  Tokyo Institute of Technology, 大学院・情報理工学研究科, 准教授 (00290867)

Project Period (FY) 2008 – 2010
Keywordsリサンプリング / マルチスケール / スケーリング則 / 仮説検定 / 信頼度 / 機械学習 / バイオインフォマティクス / モデル選択
Research Abstract

A resampling algorithm based on a scaling-law of randomness has been studied for computing a highly accurate confidence level of data analysis. In a previous study, we have proposed multiscale bootstrap method which computes an approximately unbiased confidence level (p-value) of statistical hypothesis testing in a frequentist sense. In this study, we proposed a method for computing the posterior probability in a Bayesian sense. We have shown a connection between the frequentist and the Bayesian confidence levels. We also studied a confidence level, as well as an active learning, for machine learning using the scaling-law of the randomness.

  • Research Products

    (10 results)

All 2010 2009 2008 Other

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (5 results) Book (1 results) Remarks (2 results)

  • [Journal Article] A scale-free structure prior for graphical models with applications in functional genomics2010

    • Author(s)
      P.Sheridan, T.Kamimura, H.Shimodaira
    • Journal Title

      PLoS ONE 5

      Pages: e13580

    • Peer Reviewed
  • [Journal Article] Frequentist and Bayesian measures of confidence viamultiscale bootstrap for testing three regions2010

    • Author(s)
      Hidetoshi Shimodaira
    • Journal Title

      Annals of the Institute of Statistical Mathematics 62

      Pages: 189-208

    • Peer Reviewed
  • [Presentation] Multiscale Bagging with Applications to Classification and Active Learning2010

    • Author(s)
      H.Shimodaira
    • Organizer
      The 2nd Asian Conference on Machine Learning(ACML2010)
    • Place of Presentation
      東工大 (東京)
    • Year and Date
      2010-11-10
  • [Presentation] Multiscale-bagging with Applications to Classification2010

    • Author(s)
      M.Aoki
    • Organizer
      The 2nd Asian Conference on Machine Learning (ACM L2010)
    • Place of Presentation
      東工大 (東京)
    • Year and Date
      2010-11-10
  • [Presentation] Assessing statistical reliability of LiNGAM via multiscale bootstrap2010

    • Author(s)
      Y.Komatsu
    • Organizer
      International Conference on Artificial Neural Networks(ICANN2010)
    • Place of Presentation
      Thessaloniki(ギリシャ)
    • Year and Date
      2010-09-15
  • [Presentation] Approximately unbiased tests for cone shaped regions via multiscale bootstrap2009

    • Author(s)
      Hidetoshi Shimodaira
    • Organizer
      2009 Annual Meeting, Statistical Society of Canada
    • Place of Presentation
      The University of British Columbia(カナダ)
    • Year and Date
      2009-06-03
  • [Presentation] Frequentist and Bayesian measures of confidence via multiscale bootstrap for testing three regions2008

    • Author(s)
      Hidetoshi Shimodaira
    • Organizer
      A Bayesian Approach to Statistical Inference and Its Related Topics
    • Place of Presentation
      京都大学数理解析研究所
    • Year and Date
      2008-10-22
  • [Book] 21世紀の統計科学III数理・計算の統計科学2008

    • Author(s)
      竹村彰通, 北川源四郎, 藤越康祝, 久保川達也, 塚原英敦, 田中勝人, 内田雅之, 下平英寿, 渡辺美智子, 古澄英男, 生駒哲一
    • Total Pages
      209-238
    • Publisher
      東京大学出版会
  • [Remarks] ホームページ

    • URL

      http://www.is.titech.ac.jp/~shimo/index-j.html

  • [Remarks] 大田区の区民大学(東京工業大学連携講座)「DNA情報からよみとる生物進化とランダムネス」

    • URL

      http://www.is.titech.ac.jp/~shimo/kumin2010/index-i.html

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Published: 2012-01-26   Modified: 2016-04-21  

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