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Oda Ryoya  小田 凌也

ORCIDConnect your ORCID iD *help
Researcher Number 10853682
Affiliation (Current) 2025: 広島大学, 先進理工系科学研究科(理), 准教授
Affiliation (based on the past Project Information) *help 2022 – 2025: 広島大学, 先進理工系科学研究科(理), 助教
2019 – 2023: 広島大学, 情報科学部, 特任助教
Review Section/Research Field
Principal Investigator
Basic Section 12040:Applied mathematics and statistics-related
Except Principal Investigator
Medium-sized Section 64:Environmental conservation measure and related fields / Basic Section 60030:Statistical science-related / Basic Section 57050:Prosthodontics-related / Basic Section 04010:Geography-related / Medium-sized Section 4:Geography, cultural anthropology, folklore, and related fields
Keywords
Principal Investigator
多変量線形回帰 / 多変量解析 / 変数選択法 / 高次元漸近理論 / 変数選択 / 高次元 / 一致性 / モデル選択 / 多変量モデル
Except Principal Investigator
次世代シーケンサ … More / 植物DNA / 土壌有機物 / 拡散モデル / 離散最適化 / 森林生態系資源管理 / 松枯れ拡散防止 / 放射線 / 生存時間解析 / 時空間統計モデル / fused-lasso / 地理情報システム / Fused Lasso / 情報量規準 / 時空間統計解析 / スパース推定 / Fused-Lasso / 代謝物質 / 腸内細菌 / 歯の欠損 / 認知機能 / 法科学 / 植生 / 分析化学 / DNAメタバーコーディング / 地理学 / 土壌学 / 土壌微生物 / 次世代シーケンサ(NGS) / 地域推定 / 熱分解GC-MS / 統計学的解析 / 異同識別 / 腐植 / NGS Less
  • Research Projects

    (7 results)
  • Research Products

    (43 results)
  • Co-Researchers

    (24 People)
  •  サンプル内外のどちらの予測にも対応した多変量回帰モデルにおける変数選択法の開発Principal Investigator

    • Principal Investigator
      小田 凌也
    • Project Period (FY)
      2025 – 2027
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 12040:Applied mathematics and statistics-related
    • Research Institution
      Hiroshima University
  •  Study on estimation of land use and vegetation from soil samples by organic matter analysis and plant DNA analysis

    • Principal Investigator
      柘 浩一郎
    • Project Period (FY)
      2024 – 2026
    • Research Category
      Grant-in-Aid for Scientific Research (C)
    • Review Section
      Basic Section 04010:Geography-related
    • Research Institution
      National Research Institute of Police Science
  •  Elucidating the mechanism of cognitive decline caused by tooth loss through metabolome analysis

    • Principal Investigator
      横井 美有希
    • Project Period (FY)
      2024 – 2026
    • Research Category
      Grant-in-Aid for Scientific Research (C)
    • Review Section
      Basic Section 57050:Prosthodontics-related
    • Research Institution
      Fujita Health University
  •  Optimal Pine Wilt Disease Prevention Policy in South Korea through Sustainable Forest Ecosystem Management by Discrete Optimization

    • Principal Investigator
      吉本 敦
    • Project Period (FY)
      2024 – 2028
    • Research Category
      Fund for the Promotion of Joint International Research (International Collaborative Research)
    • Review Section
      Medium-sized Section 64:Environmental conservation measure and related fields
    • Research Institution
      The Institute of Statistical Mathematics
  •  Development of consistent variable selection criteria with high-dimensional response and explanatory variables using forward-backward stepwise selection methodPrincipal Investigator

    • Principal Investigator
      Oda Ryoya
    • Project Period (FY)
      2020 – 2023
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 12040:Applied mathematics and statistics-related
    • Research Institution
      Hiroshima University
  •  Spatio-temporal risk models for Hiroshima and Nagasaki exposures by Fused-lasso

    • Principal Investigator
      山村 麻理子
    • Project Period (FY)
      2020 – 2024
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 60030:Statistical science-related
    • Research Institution
      Hiroshima University
      Radiation Effects Research Foundation
  •  Presumption of soil collecting point using geoscientific, chemical and biological method.

    • Principal Investigator
      柘 浩一郎
    • Project Period (FY)
      2019 – 2024
    • Research Category
      Grant-in-Aid for Challenging Research (Exploratory)
    • Review Section
      Medium-sized Section 4:Geography, cultural anthropology, folklore, and related fields
    • Research Institution
      National Research Institute of Police Science

All 2024 2023 2022 2021 2020

All Journal Article Presentation

  • [Journal Article] Impact of cancer and other causes of death on mortality of cancer patients: A study based on Japanese population‐based registry data2023

    • Author(s)
      Charvat Hadrien、Fukui Keisuke、Matsuda Tomohiro、Katanoda Kota、Ito Yuri
    • Journal Title

      International Journal of Cancer

      Volume: 153 Issue: 6 Pages: 1162-1171

    • DOI

      10.1002/ijc.34610

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21K17288, KAKENHI-PROJECT-22K10559, KAKENHI-PROJECT-19H01076, KAKENHI-PROJECT-23K20376, KAKENHI-PROJECT-23K21510
  • [Journal Article] An l_2,0-norm constrained matrix optimization via extended discrete first-order algorithms2023

    • Author(s)
      Ryoya Oda, Mineaki Ohishi, Yuya Suzuki, and Hirokazu Yanagihara
    • Journal Title

      Hiroshima Mathematical Journal

      Volume: -

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Journal Article] Kick-one-out-based variable selection method using ridge-type Cp criterion in high-dimensional multi-response linear regression models2023

    • Author(s)
      Ryoya Oda
    • Journal Title

      Intelligent Decision Technologies, Smart Innovation, Systems and Technologies

      Volume: -

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Journal Article] An l_2,0-norm constrained matrix optimization via extended discrete first-order algorithms2023

    • Author(s)
      Oda Ryoya、Ohishi Mineaki、Suzuki Yuya、Yanagihara Hirokazu
    • Journal Title

      Hiroshima Mathematical Journal

      Volume: -

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Journal Article] Kick-one-out-based variable selection method using ridge-type Cp criterion in high-dimensional multi-response linear regression models2023

    • Author(s)
      Oda Ryoya
    • Journal Title

      Smart Innovation, Systems and Technologies: Intelligent Decision Technologies

      Volume: -

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Journal Article] An l2,0-norm constrained matrix optimization via extended discrete first-order algorithms2023

    • Author(s)
      Oda Ryoya、Ohishi Mineaki、Suzuki Yuya、Yanagihara Hirokazu
    • Journal Title

      Hiroshima Mathematical Journal

      Volume: 53 Issue: 3 Pages: 251-267

    • DOI

      10.32917/h2021058

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K14363, KAKENHI-PROJECT-23K20376, KAKENHI-PROJECT-23K25506
  • [Journal Article] How much can screening reduce colorectal cancer mortality in Japan? Scenario-based estimation by microsimulation2021

    • Author(s)
      Kamo Ken-Ichi、Fukui Keisuke、Ito Yuri、Nakayama Tomio、Katanoda Kota
    • Journal Title

      Japanese Journal of Clinical Oncology

      Volume: 52 Issue: 3 Pages: 221-226

    • DOI

      10.1093/jjco/hyab195

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19H01076, KAKENHI-PROJECT-20H00040, KAKENHI-PROJECT-19H03913, KAKENHI-PROJECT-18K10068, KAKENHI-PROJECT-21K17288, KAKENHI-PROJECT-23K20376, KAKENHI-PROJECT-23K21510, KAKENHI-PROJECT-17H00806
  • [Journal Article] A consistent likelihood-based variable selection method in normal multivariate linear regression2021

    • Author(s)
      Oda Ryoya、Yanagihara Hirokazu
    • Journal Title

      Smart Innovation, Systems and Technologies

      Volume: 238 Pages: 391-401

    • DOI

      10.1007/978-981-16-2765-1_33

    • ISBN
      9789811627644, 9789811627651
    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-18K03415, KAKENHI-PROJECT-20K14363, KAKENHI-PROJECT-23K20376
  • [Journal Article] Coordinate descent algorithm for normal-likelihood based group Lasso in multivariate linear regression2021

    • Author(s)
      Yanagihara Hirokazu, Oda Ryoya
    • Journal Title

      Smart Innovation, Systems and Technologies

      Volume: -

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Journal Article] A consistent likelihood-based variable selection method in normal multivariate linear regression2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Journal Title

      Smart Innovation, Systems and Technologies

      Volume: -

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Journal Article] An l_2,0-norm constrained matrix optimization via extended discrete first-order algorithms2021

    • Author(s)
      Oda Ryoya, Ohishi Mineaki, Suzuki Yuya, Yanagihara Hirokazu
    • Journal Title

      Hiroshima Statistical Research Group Technical Report

      Volume: 08 Pages: 1-15

    • Open Access
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Journal Article] Coordinate descent algorithm for normal-likelihood-based group Lasso in multivariate linear regression2021

    • Author(s)
      Yanagihara Hirokazu、Oda Ryoya
    • Journal Title

      Smart Innovation, Systems and Technologies

      Volume: 238 Pages: 429-439

    • DOI

      10.1007/978-981-16-2765-1_36

    • ISBN
      9789811627644, 9789811627651
    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-18K03415, KAKENHI-PROJECT-20K14363, KAKENHI-PROJECT-23K20376
  • [Journal Article] Coordinate descent algorithm for normal-likelihood based group Lasso in multivariate linear regression.2021

    • Author(s)
      Hirokazu Yanagihara, Ryoya Oda
    • Journal Title

      Smart Innovation, Systems and Technologies (KES-IDT-21)

      Volume: in press

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Journal Article] A consistent likelihood-based variable selection method in normal multivariate linear regression.2021

    • Author(s)
      Ryoya Oda, Hirokazu Yanagihara
    • Journal Title

      Smart Innovation, Systems and Technologies (KES-IDT-21)

      Volume: in press

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Journal Article] On model selection consistency using a kick-one-out method for selecting response variables in high-dimensional multivariate linear regression2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu, Fujikoshi Yasunori
    • Journal Title

      Hiroshima Statistical Research Group Technical Report

      Volume: 07 Pages: 1-15

    • Open Access
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Journal Article] An l_2,0-norm constrained matrix optimization via extended discrete first-order algorithms2021

    • Author(s)
      Oda Ryoya, Ohishi Mineaki, Suzuki Yuya, Yanagihara Hirokazu
    • Journal Title

      Hiroshima Statistical Research Group, Technical Report

      Volume: 21-08 Pages: 1-15

    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Journal Article] On model selection consistency using a kick-one-out method for selecting response variables in high-dimensional multivariate linear regression2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu,Fujikoshi Yasunori
    • Journal Title

      Hiroshima Statistical Research Group, Technical Report

      Volume: 21-07 Pages: 1-15

    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Journal Article] Growth Curve Model with Bilinear Random Coefficients2020

    • Author(s)
      Shinpei Imori, Dietrich von Rosen, Ryoya Oda
    • Journal Title

      Sankhya A

      Volume: in press Issue: 2 Pages: 1-32

    • DOI

      10.1007/s13171-020-00204-5

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K14363, KAKENHI-PROJECT-17K12650, KAKENHI-PROJECT-23K20376
  • [Journal Article] Consistent variable selection criteria in multivariate linear regression even when dimension exceeds sample size2020

    • Author(s)
      Oda Ryoya
    • Journal Title

      Hiroshima Mathematical Journal

      Volume: 50 Issue: 3 Pages: 339-374

    • DOI

      10.32917/hmj/1607396493

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K14363, KAKENHI-PROJECT-23K20376
  • [Presentation] Asymptotic loss efficiency of a model selection criterion in a high-dimensional GMANOVA model.2024

    • Author(s)
      Ryoya Oda
    • Organizer
      統計数理研究所 共同利用 2023 年度 重点型研究 研究集会「高次元データ解析・スパース推定法・モデル選択法の開発と融合」
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] GMANOVAモデルとモデル選択規準の高次元漸近性質.2024

    • Author(s)
      小田凌也
    • Organizer
      岡山統計研究会 第182回研究会(学生セッション)全体レクチャー
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] 多変量モデルにおける複合型高次元漸近理論を用いたモデル選択規準の漸近損失有効性2023

    • Author(s)
      小田凌也
    • Organizer
      多変量統計学・統計的モデル選択の新展開
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] Kick-one-out-based variable selection method using ridge-type Cp criterion in high-dimensional multi-response linear regression models.2023

    • Author(s)
      Ryoya Oda
    • Organizer
      15th International KES Conference, IDT-23 (Invited Session: Recent Development of Multivariate Analysis and Model Selection)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] サンプル間に相関をもつ場合の2標本検定2023

    • Author(s)
      小田凌也, 栁原宏和
    • Organizer
      統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] 説明変数の個数が標本数を超える場合での一般化リッジ回帰におけるリッジパラメータ最適化法の比較2023

    • Author(s)
      桐島功希, 大石峰暉, 小田凌也, 栁原宏和
    • Organizer
      統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] Asymptotic loss efficiency of a model selection criterion in a high-dimensional GMANOVA model2023

    • Author(s)
      Ryoya Oda
    • Organizer
      統計数理研究所 共同利用 2023 年度 重点型研究 研究集会「高次元データ解析・スパース推定法・モデル選択法の開発と融合」
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] GMANOVAモデルとモデル選択規準の高次元漸近性質2023

    • Author(s)
      小田凌也
    • Organizer
      岡山統計研究会第182回研究会(学生セッション)全体レクチャー
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] Kick-one-out-based variable selection method using ridge-type Cp criterion in high-dimensional multi-response linear regression models2023

    • Author(s)
      Ryoya Oda
    • Organizer
      The 15th KES International Conference on Intelligent Decision Technologies
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] 多変量モデルにおける複合型高次元漸近理論を用いたモデル選択規準の漸近損失有効性2023

    • Author(s)
      小田凌也
    • Organizer
      多変量統計学・統計的モデル選択の新展開
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] 高次元 GMANOVA モデルにおける予測のための一般化 Cp 規準の漸近性質2022

    • Author(s)
      小田凌也
    • Organizer
      2022年度統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] Condition of GIC to the model minimizing KL-loss function in high-dimensional multivariate linear regression2022

    • Author(s)
      小田凌也
    • Organizer
      5th International Conference on Econometrics and Statistics (EcoSta 2022)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] 高次元 GMANOVA モデルにおける予測のための一般化 Cp 規準の漸近性質2022

    • Author(s)
      小田凌也
    • Organizer
      2022年度統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] Condition of GIC to the model minimizing KL-loss function in high-dimensional multivariate linear regression2022

    • Author(s)
      小田凌也
    • Organizer
      5th International Conference on Econometrics and Statistics (EcoSta 2022)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] Coordinate descent algorithm for normal-likelihood-based group Lasso in multivariate linear regression2021

    • Author(s)
      Yanagihara Hirokazu, Oda Ryoya
    • Organizer
      The 13th KES International Conference on Intelligent Decision Technologies
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] Asymptotically KL-loss efficiency of GIC in normal multivariate linear regression models under the high-dimensional asymptotic framework2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Organizer
      2021年度統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] 高次元多変量線形回帰における KL ロス最小化に基づくモデルの一致性2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Organizer
      2021年度広島大学金曜セミナー
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] A consistent likelihood-based variable selection method in normal multivariate linear regression2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Organizer
      The 13th KES International Conference on Intelligent Decision Technologies
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] A consistent variable selection method with GIC in multivariate linear regression even when dimensions are large2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Organizer
      4th International Conference on Econometrics and Statistics (EcoSta 2021)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] A consistent likelihood-based variable selection method in normal multivariate linear regression2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Organizer
      The 13th KES International Conference on Intelligent Decision Technologies
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K14363
  • [Presentation] Coordinate descent algorithm for normal-likelihood-based group Lasso in multivariate linear regression2021

    • Author(s)
      Yanagihara Hirokazu, Oda Ryoya
    • Organizer
      The 13th KES International Conference on Intelligent Decision Technologies
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] Asymptotically KL-loss efficiency of GIC in normal multivariate linear regression models under the high-dimensional asymptotic framework2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Organizer
      2021年度統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] A consistent variable selection method with GIC in multivariate linear regression even when dimensions are large2021

    • Author(s)
      Oda Ryoya, Yanagihara Hirokazu
    • Organizer
      4th International Conference on Econometrics and Statistics
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K20376
  • [Presentation] 多変量線形回帰における正規尤度に基づく簡便なモデル選択法をその一致性の評価について2020

    • Author(s)
      小田凌也
    • Organizer
      広島大学金曜セミナー
    • Data Source
      KAKENHI-PROJECT-20K14363
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  • 22.  NAKAYAMA Tomio
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    # of Collaborated Products: 1 results
  • 23.  中谷 友樹
    # of Collaborated Projects: 0 results
    # of Collaborated Products: 1 results
  • 24.  片野田 耕太
    # of Collaborated Projects: 0 results
    # of Collaborated Products: 1 results

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