revpref: Tools for Computational Revealed Preference Analysis

Tools to (i) check consistency of a finite set of consumer demand observations with a number of revealed preference axioms at a given efficiency level, (ii) compute goodness-of-fit indices when the data do not obey the axioms, and (iii) compute power against uniformly random behavior.

Version: 0.1.0
Imports: gtools
Suggests: rmarkdown, knitr
Published: 2021-07-07
Author: Khushboo Surana ORCID iD [aut, cre]
Maintainer: Khushboo Surana <khushboo.surana at york.ac.uk>
BugReports: https://github.com/ksurana21/revpref/issues
License: MIT + file LICENSE
URL: https://github.com/ksurana21/revpref
NeedsCompilation: no
Materials: README
CRAN checks: revpref results

Documentation:

Reference manual: revpref.pdf

Downloads:

Package source: revpref_0.1.0.tar.gz
Windows binaries: r-devel: revpref_0.1.0.zip, r-release: revpref_0.1.0.zip, r-oldrel: revpref_0.1.0.zip
macOS binaries: r-release (arm64): revpref_0.1.0.tgz, r-oldrel (arm64): revpref_0.1.0.tgz, r-release (x86_64): revpref_0.1.0.tgz, r-oldrel (x86_64): revpref_0.1.0.tgz

Linking:

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