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 [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-prerel: revpref_0.1.0.zip, r-release: revpref_0.1.0.zip, r-oldrel: revpref_0.1.0.zip
macOS binaries:	r-prerel (arm64): revpref_0.1.0.tgz, r-release (arm64): revpref_0.1.0.tgz, r-oldrel (arm64): revpref_0.1.0.tgz, r-prerel (x86_64): revpref_0.1.0.tgz, r-release (x86_64): revpref_0.1.0.tgz

Linking:

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