Research Interests 【 display / non-display 】

Research Interests 【 display / non-display 】

Research Areas 【 display / non-display 】

Research Areas 【 display / non-display 】

Papers 【 display / non-display 】

Papers 【 display / non-display 】

• Characterizing Healthy Dietary Practices in Japan: Insights from a 2024 Nationwide Survey and Cluster Analysis

  Shuhei Nomura, Akifumi Eguchi, Keiko Maruyama-Sakurai, Ruka Higashino, Daisuke Yoneoka, Takayuki Kawashima, Yuta Tanoue, Yumi Kawamura, Rauniyar Santosh Kumar, Takanori Fujita, Hiroaki Miyata , 2024.05

  Nutrients

  DOI

• Concentration inequality and the weak law of large numbers for the sum of partly negatively dependent <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si5.svg" display="inline" id="d1e23"><mml:mi>φ</mml:mi></mml:math>-subgaussian random variables

  Yuta Tanoue , 2024.03

  Statistics &amp; Probability Letters

  DOI

• The Efficacy of an mHealth App in Facilitating Weight Loss Among Japanese Fitness Center Members: Regression Analysis Study

  Akifumi Eguchi, Yumi Kawamura, Takayuki Kawashima, Cyrus Ghaznavi, Keiko Ishimura, Shun Kohsaka, Satoru Matsuo, Shinichiro Mizuno, Yuki Sasaki, Arata Takahashi, Yuta Tanoue, Daisuke Yoneoka, Hiroaki Miyata, Shuhei Nomura , 2023.11

  JMIR Formative Research

  DOI

• Understanding factors related to healthcare avoidance for menstrual disorders and menopausal symptoms: a cross-sectional study among women in Japan

  Manae Uchibori, Akifumi Eguchi, Cyrus Ghaznavi, Yuta Tanoue, Mami Ueta, Miho Sassa, Shu Suzuki, Sayaka Honda, Yukiko Kawata, Miho Iida, Haruka Sakamoto, Shuhei Nomura , 2023.10

  Preventive Medicine Reports

  DOI

• Estimation of the time of exposure based on interval and censored data using the <i>ε</i>‐accelerated EM algorithm

  Daisuke Yoneoka, Takayuki Kawashima, Yuta Tanoue, Shuhei Nomura, Akifumi Eguchi , 2023.08

  Statistics in Medicine

  DOI

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Grant-in-Aid for Scientific Research 【 display / non-display 】

Grant-in-Aid for Scientific Research 【 display / non-display 】

• Estimating the repayment capacity of the default company based on the credit information of multiple banks and developing its machine learning method

  Project Period (FY)： 2022/04  -  2026/03  Investigator(s): 山下 智志

  Grant-in-Aid for Scientific Research(B)  Co-Investigator  23K22160 

• 重い裾を考慮した金融リスク統合のための研究

  Project Period (FY)： 2021/04  -  2025/03  Investigator(s): 田上 悠太

  Grant-in-Aid for Young Scientists  Principal Investigator  21K13328 

• Development of a Practically Usable Highly Accurate LGD Estimation Model Using the Integrated Database of Regional Banks

  Project Period (FY)： 2018/04  -  2022/03  Investigator(s): Tanoue Yuta

  Grant-in-Aid for Young Scientists  Principal Investigator  18K12873 

  The Basel accords, which aim to strengthen the soundness of the international financial system, require banks to estimate various risks and accumulate capital to cover them. This study was conducted to improve the estimation accuracy of credit risk of bank claims, especially LGD estimation. The results of this study confirm the usefulness of nonlinear models in LGD estimation. We also tested the effectiveness of transfer learning, macroeconomic variables, and business history. We also conducted research on variable selection methods in LGD estimation, which involves a large number of explanatory variables.

• 地銀統合データベースを用いた高精度LGD推定モデルとシステム実装

  Project Period (FY)： 2017/08  -  2019/03  Investigator(s): 田上 悠太

  Grant-in-Aid for Research Activity start-up  Principal Investigator  17H07322 

Lesson Subject 【 display / non-display 】

Lesson Subject 【 display / non-display 】