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
DESCRIPTION
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 271 downloads 8 exports 1 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK112
source / vignettesOK153
linux-release-x86_64OK113
macos-release-arm64OK119
macos-oldrel-arm64OK228
windows-develOK65
windows-releaseOK66
windows-oldrelOK106
wasm-releaseOK111

Exports:genMatlogitAttelogitSimurAtterevealAtterevealPrefrevealPrefModelsumData

Dependencies:MASS