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2013 Fiscal Year Final Research Report

New Developments of Multivariate Statistical Methodologies - High Speed, Robustness, and High Accuracy

Research Project

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Project/Area Number 23650142
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeMulti-year Fund
Research Field Statistical science
Research InstitutionUniversity of Tsukuba

Principal Investigator

AOSHIMA Makoto  筑波大学, 数理物質系, 教授 (90246679)

Co-Investigator(Kenkyū-buntansha) YATA Kazuyoshi  筑波大学, 数理物質系, 助教 (90585803)
AKAHIRA Masafumi  筑波大学, 名誉教授 (70017424)
Project Period (FY) 2011 – 2013
Keywords異常値 / クラスター分析 / 判別分析 / 多変量解析 / クロスデータ行列法 / 高次モーメント / 非ガウス / 回帰分析
Research Abstract

In this research project, we aim to develop new multivariate statistical methods satisfying the criteria of high speed, robustness and high accuracy for inferences on modern data. We provided three multivariate statistical methods to ensure robustness and high accuracy with low computational cost even for non-Gaussian, contaminated models. The findings of this research are as follows: (1) Developments of high-speed and highly accurate classification methods using higher moments. (2) Developments of high-speed and highly accurate variable selection and outlier detection methods. (3) Intrinsic space analysis in a contaminated data space.

  • Research Products

    (8 results)

All 2014 2013 2012 Other

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

  • [Journal Article] A distance-based, misclassification rate adjusted classifier for multiclass, high-dimensional data2013

    • Author(s)
      Aoshima, M., Yata, K
    • Journal Title

      Annals of the Institute of Statistical Mathematics

      Volume: (印刷中)

    • DOI

      10.1007/s10463-013-0435-8

    • Peer Reviewed
  • [Journal Article] A higher order approximation to a percentage point of the distribution of a noncentral t-statistic without the normality assumption. Commun2013

    • Author(s)
      Akahira, M., Ohyauchi, N., Kawai, S
    • Journal Title

      Statist.-Simula

      Volume: 42 Pages: 2086-2105

    • DOI

      10.1080/03610918.2012.695841

    • Peer Reviewed
  • [Presentation] Effective Classifiers for High-Dimensional Data2014

    • Author(s)
      Yata, K
    • Organizer
      Workshop on Statistics for High-Dimensional and Dependent Data
    • Place of Presentation
      National Taiwan University (中華民国)
    • Year and Date
      2014-03-21
  • [Presentation] Asymptotic comparison of the MLE and MCLE of a natural parameter up to the second order for a truncated exponential family of distributions2014

    • Author(s)
      赤平 昌文
    • Organizer
      日本数学会2014年度年会
    • Place of Presentation
      学習院大学(東京都)
    • Year and Date
      2014-03-17
  • [Presentation] Effective Methodologies for High-Dimensional Data and their Applications2013

    • Author(s)
      Aoshima, M
    • Organizer
      STOR Colloquium
    • Place of Presentation
      University of North Carolina (アメリカ合衆国)
    • Year and Date
      2013-07-15
  • [Presentation] Effective Classification for High-Dimension, Non-Gaussian Data2012

    • Author(s)
      Aoshima, M
    • Organizer
      The 2nd IMS Asia Pacific Rim Meeting
    • Place of Presentation
      つくば国際会議場(茨城県)
    • Year and Date
      2012-07-03
  • [Presentation] Discussion on Professor Shelemyahu Zacks' Talk2012

    • Author(s)
      Aoshima, M
    • Organizer
      The Sixth International Workshop on Applied Probability
    • Place of Presentation
      Inbal Hotel Jerusalem (イスラエル国)
    • Year and Date
      2012-06-13
  • [Remarks]

    • URL

      http://www.math.tsukuba.ac.jp/~aoshimalab/

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Published: 2015-06-25  

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