Minami, Mihoko

写真a

Affiliation

Faculty of Science and Technology, Department of Mathematics (Yagami)

Position

Professor

Related Websites

Career 【 Display / hide

  • 1982.04
    -
    1987.11

    Nihon Univac Co.Ltd.

  • 1995.04
    -
    1999.03

    Science University of Tokyo, Faculty of Science, Department of Applied Mathematics, Assistant Professor

  • 1999.04
    -
    2009.03

    The Institute of Statistical Mathematics, Department of Mathematical Analysis and Statistical Inference, Associate Professor

  • 1999.04
    -
    2009.03

    The Graduate University for Advanced Studies, School of Multidisciplinary Sciences, Department of Statistical Science, Associate Professor

  • 2001.09
    -
    2008.03

    Keiou University, Faculty of Science and Technology, Part-time Lecturer

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Academic Background 【 Display / hide

  • 1982.03

    Ochanomizu University, Faculty of Science, Department of Mathematics

    University, Graduated

  • 1990.06

    University of California, San Diego Master course, Department of Mathematics

    United States, University, Graduated

  • 1993.12

    University of California, San Diego Department of Mathematics, Ph.D. course, Department of Mathematics

    United States, University, Graduated

Academic Degrees 【 Display / hide

  • Ph.D., University of California, San Diego, Coursework, 1993.12

 

Research Areas 【 Display / hide

  • Informatics / Statistical science (Statistical Science)

Research Themes 【 Display / hide

  • 環境リスク解析, 

    2009.04
    -
    Present

  • Cyclic regression smoothing spline for environmental data, 

    2009
    -
    Present

  • Regression and Classification problem for distributions, 

    2008
    -
    Present

  • Feature extraction method from very non-normal data, 

    2007
    -
    Present

     View Summary

    海洋生物の混獲数データのように非正規性の強いデータから特徴量を抽出する統計手法の研究。視点をかえると非正規データの次元の削減問題と捉えることができる

  • 生物資源評価, 

    2005.04
    -
    Present

 

Books 【 Display / hide

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Papers 【 Display / hide

  • Exposure to PM2.5 and Lung Function Growth in Pre- and Early-Adolescent Schoolchildren A Longitudinal Study Involving Repeated Lung Function Measurements in Japan

    Toru Takebayashi, Masataka Taguri, Hiroshi Odajima et al.

    Annals of the American Thoracic Society 19 ( 5 ) 763 - 772 2022.05

    Research paper (scientific journal), Accepted

  • Causal Subclassification Tree Algorithm and Robust Causal Effect Estimation via Subclassification

    Tomoshige Nakamura, Mihoko Minami

    International Journal of Statistics and Probability 10 ( 1 ) 40 - 57 2020.11

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  1927-7032

  • Cluster analysis methods applied to daily vessel location data to identify cooperative fishing among tuna purse-seiners

    Lennert-Cody C.E., Maunder M.N., Román M.H., Xu H., Minami M., Lopez J.

    Environmental and Ecological Statistics (Environmental and Ecological Statistics)  27 ( 4 ) 649 - 664 2020.08

    Research paper (scientific journal), Accepted,  ISSN  13528505

     View Summary

    © 2020, Springer Science+Business Media, LLC, part of Springer Nature. Management of large-scale pelagic fisheries relies heavily on fishery data to provide information on tuna population status because, for widely distributed populations, the cost of collecting survey data is often prohibitively high. However, fishery data typically do not provide direct information on interactions among fishing vessels, and thus methods of analysis often assume that vessels operate independently, despite the belief that cooperative fishing occurs. Cluster analysis methods were applied to daily vessel location data collected by onboard fisheries observers to identify groups of tuna purse-seine vessels searching for fish close to each other in space. Some vessel groups were found to reoccur through time, both on daily and monthly or longer time scales. This temporal persistence and reoccurrence are interpreted as an indication of cooperative fishing. Results indicate that there may be multiple layers of vessel interactions, from groups of a few vessels to networks of larger numbers of vessels. The use of reoccurring vessel group characteristics to study the temporal and spatial persistence of areas of high tuna abundance is discussed.

  • Estimation of risk contributions with MCMC

    Koike T., Minami M.

    Quantitative Finance (Quantitative Finance)  19 ( 9 ) 1579 - 1597 2019.04

    Research paper (scientific journal), Accepted,  ISSN  14697688

     View Summary

    © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. Determining risk contributions of unit exposures to portfolio-wide economic capital is an important task in financial risk management. Computing risk contributions involves difficulties caused by rare-event simulations. In this study, we address the problem of estimating risk contributions when the total risk is measured by value-at-risk (VaR). Our proposed estimator of VaR contributions is based on the Metropolis-Hasting (MH) algorithm, which is one of the most prevalent Markov chain Monte Carlo (MCMC) methods. Unlike existing estimators, our MH-based estimator consists of samples from the conditional loss distribution given a rare event of interest. This feature enhances sample efficiency compared with the crude Monte Carlo method. Moreover, our method has consistency and asymptotic normality, and is widely applicable to various risk models having a joint loss density. Our numerical experiments based on simulation and real-world data demonstrate that in various risk models, even those having high-dimensional (≈500) inhomogeneous margins, our MH estimator has smaller bias and mean squared error when compared with existing estimators.

  • Max-Stable Processによる年最大日降水量データ解析

    Ayato Kashiyama, Mihoko Minami

    Japanese Journal of Applied Statistics (応用統計学会)  47 ( 2&3 ) 51 - 70 2018.12

    Accepted,  ISSN  0285-0370

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Papers, etc., Registered in KOARA 【 Display / hide

Presentations 【 Display / hide

  • Regression Tree and Clustering for Distributions, and Homogeneous Structure of Population Characteristics

    Mihoko Minami

    Waseda International Symposium (Waseda University ) , 

    2021.03

    Waseda University

  • 分布に基づいたクラスタリングに対する階層手順による多重検定

    南美穂子, Cleridy E. Lennert-Cody

    2020年度統計関連学会連合大会, 

    2020.09

    Oral presentation (general)

  • Jensen-Shannon ダイバージェンスを用いた分布に対する回帰樹,クラスタリング,多重比較

    南美穂子, Cleridy E. Lennert-Cody

    2019年度統計関連学会連合大会, 

    2019.09

  • Clustering methods for distributions and partioning of space.

    Mihoko Minami, Cleridy E. Lennert-Cody

    統計数理研究所共同研究集会「環境・生態データと統計解析」, 

    2018.10

  • Analysis of Decision Makers' Strategies

    Mihoko Minami

    Joint Statistical Meeting 2018 (Vancouver, Canada) , 

    2018.07

    Oral presentation (general), American Statistical Association

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Research Projects of Competitive Funds, etc. 【 Display / hide

  • 分布データの解析手法,統計的推測法の提案と生物資源評価,生態・環境データへの応用

    2021.04
    -
    2026.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), Principal investigator

  • 環境リスク解析・生物資源評価のための統計的モデリングと解析手法

    2017.04
    -
    2021.03

    独立行政法人 日本学術振興会, Grant-in-Aid for Scientific Research, Research grant, Principal investigator

     View Summary

    本研究は,環境リスク解析と生物資源評価のための,統計的モデリングと解析手法の提案を目的とする.

Awards 【 Display / hide

  • Jacob Wolfowitz prize

    Mihoko Minami and Kunio Shimizu, 2001.12, American Journal of Mathematical and Management Sciences, ML and REML estimation of Matusita's measure for two bivariate normal distributions with missing observations

 

Courses Taught 【 Display / hide

  • TOPICS IN STATISTICAL SCIENCES A

    2022

  • TOPICS IN LIFE INSURANCE MATHEMATICS

    2022

  • SEMINAR IN STATISTICAL SCIENCES

    2022

  • MATHEMATICS 2A

    2022

  • MATHEMATICAL STATISTICS 1 AND ITS EXERCISE

    2022

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Courses Previously Taught 【 Display / hide

  • データサイエンス特別講義

    慶應義塾大学理工学研究科

    2019.04
    -
    2020.03

    Autumn Semester

  • 数理統計学第二

    慶應義塾大学理工学部

    2019.04
    -
    2020.03

    Autumn Semester

  • 数学2B

    慶應義塾大学理工学部

    2019.04
    -
    2020.03

    Autumn Semester

  • 統計輪講

    Keio University

    2014.04
    -
    2015.03

    Autumn Semester, Within own faculty, 1h

  • データ解析同演習

    Keio University

    2014.04
    -
    2015.03

    Autumn Semester, Seminar, Within own faculty, 1h

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Social Activities 【 Display / hide

  • 微小粒子状物質等疫学調査研究検討会 環境省 水・大気環境局

    2010.09
    -
    Present
  • AISM 編集委員会

    2006.04
    -
    2014.03

Memberships in Academic Societies 【 Display / hide

  • 国際計量生物学会 IBC2012 実行委員会, 

    2009.11
    -
    2012.09
  • 国際計量生物学会 IBC2010 国際プログラム委員会, 

    2007.07
    -
    2010.12
  • 2004年度統計関連学会連合大会 事務局, 

    2003.10
    -
    2004.09
  • 2003年度統計関連学会連合大会 事務局, 

    2002.10
    -
    2003.09
  • Fourth International Sysmposium on Independent Component Analysis and blind source Separation (ICA2003), 

    2002.04
    -
    2003.04

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Committee Experiences 【 Display / hide

  • 2022.04
    -
    2024.03

    委員長, 日本統計学会多様性推進特別委員会

  • 2021.09
    -
    2023.09

    委員長, 日本統計学会学会活動特別委員会

  • 2021.04
    -
    2023.03

    代議員, 日本統計学会

  • 2020.10
    -
    2026.09

    連携会員, 日本学術会議

  • 2020.05
    -
    2024.05

    編集理事, 応用統計学会

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