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:Matias D. Cattaneo, Paul Cheung, Xinwei Ma, Yusufcan Masatlioglu, Elchin Suleymanov

ramchoice_2.2.tar.gz
ramchoice_2.2.zip(r-4.7)ramchoice_2.2.zip(r-4.6)ramchoice_2.2.zip(r-4.5)
ramchoice_2.2.tgz(r-4.6-any)ramchoice_2.2.tgz(r-4.5-any)
ramchoice_2.2.tar.gz(r-4.7-any)ramchoice_2.2.tar.gz(r-4.6-any)
ramchoice_2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
ramchoice/json (API)

# Install 'ramchoice' in R:
install.packages('ramchoice', repos = c('https://xinweima.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • ramdata - Ramdata: Simulated Choice Data

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 3 scripts 154 downloads 8 exports 1 dependencies

Last updated from:e882a9e7a0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK105
source / vignettesOK147
linux-release-x86_64OK115
macos-release-arm64OK150
macos-oldrel-arm64OK199
windows-develOK98
windows-releaseOK68
windows-oldrelOK67
wasm-releaseOK109

Exports:genMatlogitAttelogitSimurAtterevealAtterevealPrefrevealPrefModelsumData

Dependencies:MASS