Updated on 2026/03/14

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KONNO YOSHIHIKO
 
Organization
Graduate School of Science Department of Mathematics Professor
School of Science Department of Mathematics
Title
Professor
Affiliation
Institute of Science
Profile
KONNO Yoshihiko, Professor of Osaka Metropolitan University and Professor Emeritus of Japan Women's University, received the degree of a B.S. in mathematics from University of Tsukuba, Japan in 1984 and a M.S. in mathematics from the same university in 1986. He earned a degree of Ph.D. from Institute of Mathematics, University of Tsukuba in 1992. He was an assistant researcher in Institute of Mathematics, University of Tsukuba from 1988 to 1990 and a lecturer in Department of Manageing, Ishinomaki Senshu University from 1990 to 1993. He was an Associate Professor at Chiba University from 1993 to 2003 and Japan Women's University from 2003 to 2006. He was a Professor in Department of Mathematical ans Physical Sciences at Japan Women's University from 2006 to 2022. He joined the faculty at Department of Mathematics, Osaka Metropolitan University in April 2022. He also spent two months in July and August of 1994 at Department of Mathematics and Statistics, Carleton University, and a year in 1997-1998 as a visiting fellow at the Department of Statistics, University of Washington. Until now he has not received any medals and will not receive it in the future, too. KONNO is a multivariate-analysist who gets tangled up in difference product of eigenvalues and Shrinkage in Statistics. His resarch interest includes finite-sample estimation problems in multivariate analysis and non-asymptotic approach for inference theory for high-dimensional statistical models.
Affiliation campus
Sugimoto Campus

Position

  • Graduate School of Science Department of Mathematics 

    Professor  2022.04 - Now

  • School of Science Department of Mathematics 

    Professor  2022.04 - Now

Degree

  • 理学博士 ( University of Tsukuba )

Research Areas

  • Natural Science / Applied mathematics and statistics  / Statistical Inference theory

Research Interests

  • 統計的推測理論

Research subject summary

  • Research on the optimality of estimation methods, which are the basis of mathematical statistics

Professional Memberships

  • the Japanese Association of Financial Econometric and Engineering

  • Institute of Mathematical Statistics

  • International Statistical Institute

  • the American Statistcal Association

  • Japanese Society of Applied Statistics

  • Mathematical Society of Japan

  • Japan Statistical Society

  • Japanese Society of Computational Statistics

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Papers

  • Pretest Estimator for Individual Normal Means with Meta-analytic Data Reviewed

    Taketomi Nanami, Chang Yuan-Tsung, Konno Yoshihiko, Mori Mihoko, Emura Takeshi

    Journal of the Japan Statistical Society, Japanese Issue   54 ( 2 )   73 - 108   2025.03( ISSN:03895602 ( eISSN:21891478

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    <p>Meta-analysis is a statistical method to summarize quantitative results from a set of published studies. Meta-analysis often assumes that the outcomes of all individual studies have a common mean and estimates the common mean based on the results of each study. On the other hand, meta-analysis sometimes shows an updated estimate of individual study. This paper is a review article for estimation of individual normal means based on pretest estimators using meta-analytic data. New results on the bias, mean squared error, and variance of the pretest estimator are also included in this paper. The use of the R package: <i>meta.shrinkage </i>is also described. An example of the application to eye allergic reaction data during anatomy practice is also reported.</p>

    DOI: 10.11329/jjssj.54.73

    CiNii Research

  • Pretest Estimator for Individual Normal Means with Meta-analytic Data Reviewed

    Nanami Taketomi, Yuan-Tsung Chang, Yoshihiko Konno, Mihoko Mori, Takeshi Emura

    Journal of the Japan Statistical Society   54 ( 2 )   73 - 108   2025.03

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:Domestic journal  

    DOI: https://doi.org/10.11329/jjssj.54.73

    Other URL: https://www.jstage.jst.go.jp/article/jjssj/54/2/54_73/_pdf/-char/ja

  • An adaptive singular value shrinkage for estimation problem of low-rank matrix mean with unknown covariance matrix

    Konno Y.

    Japanese Journal of Statistics and Data Science   7 ( 1 )   455 - 464   2024.06

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  • Confidence interval for normal means in meta-analysis based on a pretest estimator

    Taketomi N.

    Japanese Journal of Statistics and Data Science   7 ( 1 )   537 - 568   2024.06

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  • Confidence interval for normal means in meta-analysis based on a pretest estimator Reviewed

    Nanami Taketomi, Yuan-Tsung Chang, Yoshihiko Konno, Mihoko Mori,Takeshi Emura

    Japanese Journal of Statistics and Data Science   7   537 - 568   2024

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    International / domestic magazine:Domestic journal  

    DOI: https://doi.org/10.1007/s42081-023-00221-2

  • An adaptive singular value shrinkage for estimation problem of low-rank matrix mean with unknown covariance matrix Invited Reviewed

    Yoshihiko Konno

    Japanese Journal of Statistics and Data Science   7   455 - 464   2024

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    International / domestic magazine:Domestic journal  

    DOI: https://doi.org/10.1007/s42081-023-00223-0

  • A class of general pretest estimators for the univariate normal mean Reviewed

    Jia-Han Shih , Yoshihiko Konno , Yuan-Tsung Chang,Takeshi Emura

    Communications in Statistics - Theory and Methods   52 ( 8 )   2538 - 2561   2023.08

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    DOI: https://doi.org/10.1080/03610926.2021.1955384

  • Copula-based estimation methods for a common mean vector for bivariate meta-analyses

    Jia-Han Shih, Yoshihiko Konno, Yuan-Tsung Chang,Takeshi Emura

    Symmetry   14 ( 2 )   186   2022.01

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    Publishing type:Research paper (scientific journal)   International / domestic magazine:International journal  

    DOI: https://doi.org/10.3390/sym14020186

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Presentations

  • Shrinkage Estimators in Multivariate Normal Distributions with Block Compound Symmetry Structures International conference

    KONNO Yoshihiko

    The 13th Conference of the IASC-ARS   2025.12  IASC-ARS

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    Presentation type:Oral presentation (general)  

    Venue:Ho Chi Minh City, Vietnam  

    This talk develops shrinkage estimators for the mean vec-
    tor of a multivariate normal distribution under structured covari-
    ance models. Since Stein (1956), many shrinkage estimators have
    been proposed for simultaneous mean estimation, but much of
    this work has not fully exploited patterned covariance structures
    such as the intraclass model and its multivariate extension, the
    block compound symmetry structure. These covariance patterns
    arise naturally from linear representations in matrix decomposi-
    tions as well as from invariance under group actions, and they
    can be characterized within the framework of symmetric cones
    and Euclidean Jordan algebras. Building on these perspectives,
    we derive SURE-based shrinkage procedures that improve upon
    the usual maximum likelihood estimator under both intraclass
    and block compound symmetry structures. The proposed meth-
    ods are analyzed in terms of their theoretical properties and are
    evaluated numerically against classical shrinkage estimators. The
    results demonstrate substantial risk reduction across a range of
    settings.

Grant-in-Aid for Scientific Research

  • Mathematical Aspects of Statistical modeling and inference for high-dimensional data

    Fund for the Promotion of Joint International Research (International Collaborative Research)  2027

  • Mathematical Aspects of Statistical modeling and inference for high-dimensional data

    Fund for the Promotion of Joint International Research (International Collaborative Research)  2026

  • Mathematical Aspects of Statistical modeling and inference for high-dimensional data

    Fund for the Promotion of Joint International Research (International Collaborative Research)  2025

  • Mathematical Aspects of Statistical modeling and inference for high-dimensional data

    Fund for the Promotion of Joint International Research (International Collaborative Research)  2024

  • 多変量解析における統計的推測理論の新たな地平の開拓

    Grant-in-Aid for Scientific Research(C)  2023

  • 多変量解析における統計的推測理論の新たな地平の開拓

    Grant-in-Aid for Scientific Research(C)  2022

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Outline of education staff

  • Elementary Statistics and Mathematical Statistics

Charge of on-campus class subject

  • 海外特別研究3

    2025   Intensive lecture   Graduate school

  • 海外特別研究3

    2025   Intensive lecture   Graduate school

  • 海外特別研究4

    2025   Intensive lecture   Graduate school

  • 海外特別研究5

    2025   Intensive lecture   Graduate school

  • 数学特別研究3B

    2025   Intensive lecture   Graduate school

  • 数学特別研究4B

    2025   Intensive lecture   Graduate school

  • 数学特別研究5B

    2025   Intensive lecture   Graduate school

  • 確率統計論ゼミナール

    2025   Intensive lecture   Graduate school

  • 確率統計論演習1

    2025   Intensive lecture   Graduate school

  • 確率統計論演習2

    2025   Intensive lecture   Graduate school

  • 海外特別研究1

    2025   Intensive lecture   Graduate school

  • 海外特別研究2

    2025   Intensive lecture   Graduate school

  • 数学特別研究1B

    2025   Intensive lecture   Graduate school

  • 数学特別研究2B

    2025   Intensive lecture   Graduate school

  • 数学卒業研究B

    2025   Intensive lecture   Undergraduate

  • 統計学基礎2

    2025   Weekly class   Undergraduate

  • 統計学基礎

    2025   Intensive lecture   Undergraduate

  • 統計学基礎1

    2025   Weekly class   Undergraduate

  • 統計学基礎1

    2025   Weekly class   Undergraduate

  • 確率統計I

    2025   Weekly class   Undergraduate

  • 数学特別研究3A

    2025   Intensive lecture   Graduate school

  • 数学特別研究4A

    2025   Intensive lecture   Graduate school

  • 数学特別研究5A

    2025   Intensive lecture   Graduate school

  • 数学概論A

    2025   Weekly class   Graduate school

  • 統計解析特論B

    2025   Weekly class   Graduate school

  • 数学特別研究1A

    2025   Intensive lecture   Graduate school

  • 数学特別研究2A

    2025   Intensive lecture   Graduate school

  • 数理統計学1

    2025   Weekly class   Undergraduate

  • 数学卒業研究A

    2025   Intensive lecture   Undergraduate

  • 応用統計学

    2024   Weekly class   Undergraduate

  • 数理科学演習II

    2024   Intensive lecture   Undergraduate

  • 数理科学卒業研究

    2024   Intensive lecture   Undergraduate

  • 統計学基礎2

    2024   Weekly class   Graduate school

  • 確率統計ゼミナール

    2024   Intensive lecture   Graduate school

  • 海外特別研究3

    2024   Intensive lecture   Graduate school

  • 海外特別研究4

    2024   Intensive lecture   Graduate school

  • 海外特別研究5

    2024   Intensive lecture   Graduate school

  • 数学特別研究3B

    2024   Intensive lecture   Graduate school

  • 数学特別研究4B

    2024   Intensive lecture   Graduate school

  • 数学特別研究5B

    2024   Intensive lecture   Graduate school

  • 確率統計論演習1

    2024   Intensive lecture   Graduate school

  • 確率統計論演習2

    2024   Intensive lecture   Graduate school

  • 海外特別研究1

    2024   Intensive lecture   Graduate school

  • 海外特別研究2

    2024   Intensive lecture   Graduate school

  • 数学特別研究1B

    2024   Intensive lecture   Graduate school

  • 数学特別研究2B

    2024   Intensive lecture   Graduate school

  • 数理統計学2

    2024   Weekly class   Undergraduate

  • 確率統計I

    2024   Weekly class   Undergraduate

  • 数理科学演習I

    2024   Intensive lecture   Undergraduate

  • 統計学基礎1

    2024   Weekly class   Graduate school

  • 統計学基礎1

    2024   Weekly class   Graduate school

  • 数学特別研究3A

    2024   Intensive lecture   Graduate school

  • 数学特別研究4A

    2024   Intensive lecture   Graduate school

  • 数学特別研究5A

    2024   Intensive lecture   Graduate school

  • 統計解析特論A

    2024   Weekly class   Graduate school

  • 数学特別研究1A

    2024   Intensive lecture   Graduate school

  • 数学特別研究2A

    2024   Intensive lecture   Graduate school

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Charge of off-campus class subject

  • 数理統計学1

    2021.09
    -
    2027.03
    Institution:Rikkyo University

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    Level:Postgraduate 

  • 統計数学特別講義第二

    2021.04
    -
    2026.08
    Institution:Chuo University

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    Level:Postgraduate 

Faculty development activities

  • 教育改革委員  2025

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    教育改革に関わる全学に会議に出席した.

Number of instructed thesis, researches

  • 2024

    Number of instructed the graduation thesis:Number of graduation thesis reviews:0

    [Number of instructed the Master's Program] (previous term):[Number of instructed the Master's Program] (letter term):0

    [Number of master's thesis reviews] (chief):[Number of master's thesis reviews] (vice-chief):2

    [Number of doctoral thesis reviews] (chief):[Number of doctoral thesis reviews] (vice-chief):2

  • 2023

    Number of instructed the graduation thesis:Number of graduation thesis reviews:0

    [Number of instructed the Master's Program] (previous term):[Number of instructed the Master's Program] (letter term):0

    [Number of master's thesis reviews] (chief):[Number of master's thesis reviews] (vice-chief):0

    [Number of doctoral thesis reviews] (chief):[Number of doctoral thesis reviews] (vice-chief):0

  • 2022

    Number of instructed the graduation thesis:Number of graduation thesis reviews:0

    [Number of instructed the Master's Program] (previous term):[Number of instructed the Master's Program] (letter term):0

    [Number of master's thesis reviews] (chief):[Number of master's thesis reviews] (vice-chief):0

    [Number of doctoral thesis reviews] (chief):[Number of doctoral thesis reviews] (vice-chief):0

Academic Activities

  • Associate editor of Institute of Statistical Mathematics

    Role(s): Peer review

    2022.04 - 2025.03

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    Type:Scientific advice/Review