Skip to content

Rising-Stars-by-Sunshine/stats201-portfolio

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

49 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Project information

  • Author: [First Name][Last Name], [Major], [Class], Duke Kunshan University
  • Instructor: Prof. Luyao Zhang, Duke Kunshan University
  • Disclaimer: Submissions to the Problem Set 1 for STATS201 Introduction to Machine Learning for Social Science, 2023 Spring Term (Seven Week - First) instructed by Prof. Luyao Zhang at Duke Kunshan University.
  • Acknowledgments: How to Acknowledge? [notes: please include all professors, students, and staff who have contributed to your completetion of the project.]
  • Project Summary:
    • [Summarize the Background/Motivation]
    • [Research Questions]
    • [Application Scenario (Data Source)]
    • [Methodology]
    • [Results]
    • [Intellectual Merits and Practical impacts of your project.]

Table of Contents

  • data
  • code
  • spotlight

Data

  • Data Source:
  • Queried Data
  • Processed Data
  • ...

Code

  • Query Data
  • Process Data
  • Analyze Data
  • ...

Spotlight

  • Figures
  • Posters
  • Slides
  • Presentations
  • Review articles
  • Media appearance

References

Data Source

  • Data Source Title and URL

Code Source

  • Code Source Title and URL

Articles

  • Article Source Title and URL

Literature

Levin, Dan, and Luyao Zhang. 2020. “Bridging Level-K to Nash Equilibrium.” The Review of Economics and Statistics 104 (6): 1329–40. https://doi.org/10.1162/rest_a_00990.

@article{levin2022bridging,
  title={Bridging level-k to nash equilibrium},
  author={Levin, Dan and Zhang, Luyao},
  journal={Review of Economics and Statistics},
  volume={104},
  number={6},
  pages={1329--1340},
  year={2022},
  publisher={MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info~…}
}

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%