Package: ramchoice 2.2
ramchoice: Revealed Preference and Attention Analysis in Random Limited Attention Models
It is widely documented in psychology, economics and other disciplines that socio-economic agent may not pay full attention to all available alternatives, rendering standard revealed preference theory invalid. This package implements the estimation and inference procedures of Cattaneo, Ma, Masatlioglu and Suleymanov (2020) <arxiv:1712.03448> and Cattaneo, Cheung, Ma, and Masatlioglu (2022) <arxiv:2110.10650>, which utilizes standard choice data to partially identify and estimate a decision maker's preference and attention. For inference, several simulation-based critical values are provided.
Authors:
ramchoice_2.2.tar.gz
ramchoice_2.2.zip(r-4.5)ramchoice_2.2.zip(r-4.4)ramchoice_2.2.zip(r-4.3)
ramchoice_2.2.tgz(r-4.4-any)ramchoice_2.2.tgz(r-4.3-any)
ramchoice_2.2.tar.gz(r-4.5-noble)ramchoice_2.2.tar.gz(r-4.4-noble)
ramchoice_2.2.tgz(r-4.4-emscripten)ramchoice_2.2.tgz(r-4.3-emscripten)
ramchoice.pdf |ramchoice.html✨
ramchoice/json (API)
| # Install 'ramchoice' in R: |
| install.packages('ramchoice', repos = c('https://xinweima.r-universe.dev', 'https://cloud.r-project.org')) |
- ramdata - Ramdata: Simulated Choice Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:e882a9e7a0. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | OK | Oct 31 2024 |
| R-4.5-linux | OK | Oct 31 2024 |
| R-4.4-win | OK | Oct 31 2024 |
| R-4.4-mac | OK | Oct 31 2024 |
| R-4.3-win | OK | Oct 31 2024 |
| R-4.3-mac | OK | Oct 31 2024 |
Exports:genMatlogitAttelogitSimurAtterevealAtterevealPrefrevealPrefModelsumData
Dependencies:MASS
