Torrent details for "Adams C. Game Theory for Applied Econometricians. Data Analytics…" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
35.9 MB
Info Hash:
6C458A3C76495B4431C9D53E0A8A88442002CE23
Added By:
Added:
April 20, 2026, 3:26 a.m.
Stats:
|
(Last updated: April 20, 2026, 3:26 a.m.)
| File | Size |
|---|---|
| ['Grolemund G. Hands-On Programming with R. Write Your Own Functions...2014.pdf'] | 0 bytes |
| ['Adams C. Game Theory for Applied Econometricians. Data Analytics with R 2025.pdf'] | 0 bytes |
| ['Wickham H. R for Data Science. Import, Tidy, Transform, Visualize,...2ed 2023.pdf'] | 0 bytes |
Name
DL
Uploader
Size
S/L
Added
-
35.9 MB
[39
/
31]
2026-04-20
| Uploaded by andryold1 | Size 35.9 MB | Health [ 39 /31 ] | Added 2026-04-20 |
NOTE
SOURCE: Adams C. Game Theory for Applied Econometricians. Data Analytics with R 2025
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format Over the last 30 years the practice and use of game theory has changed dramatically, yet textbooks continue to present game theory with algebraic formalism and toy models. This book, on the other hand, illustrates game theory concepts using real-world data and analyses problems with real policy implications. The focus is on applying current learning to real world problems by providing an introduction to game theory and econometric analysis based on game theoretic principles using the computer language R. The book teaches game theory through code, in particular, it will use the scripting language R. It is not primarily aimed at teaching R. Rather, it is primarily aimed at teaching game theory. This idea of using computer programming as a tool of instruction goes back to at least Seymour Papert and MIT's AI lab in the 1970s.1 Papert helped develop a programming language called Logo. The goal of Logo was to teach geometry by programming how a turtle moves around the screen. You may have used one of the offspring of Logo, such as Scratch or Lego Mindstorms. The book uses Papert's ideas to teach game theory. You will learn the math of the game or estimation method and then how to program that game or estimation method. The book makes particular use of the computer's ability to simulate data. This allows us to experiment with more complicated and realistic games than is possible with pen and paper. The book is written in RStudio using Sweave. Sweave allows LaTeX to be integrated into R. LaTeX is a free type-setting language that is designed for writing math. Much of the code that is used in the book is actually presented in the book. The book covers the standard topics of an introductory game theory course including dominant strategies, Nash equilibrium and Bayes Nash equilibrium. It layers on top of this an approach to statistics and econometrics called Structural Modeling. In this approach, key parameter estimates rely upon game theoretic analysis. The real-world examples used to illustrate these concepts vary in scope and include an analysis of bargaining between hospitals and insurers, equilibrium entry of retail tire stores, bid rigging in timber auctions and contracts in 19th century whaling. Introduction Static Games of Complete Information Games Nash Equilibrium Oligopoly Empirical Entry Games Mixed Strategies II Dynamic Games of Complete Information Dynamic Games Repeated Games Bargaining III Static Games of Incomplete Information Bayes Nash Equilibrium Auctions Auctions with Affiliated Valuations IV Dynamic Games of Incomplete Information Moral Hazard Adverse Selection
×