eaf: Plots of the Empirical Attainment Function

Computation and visualization of the empirical attainment function (EAF) for the analysis of random sets in multi-criterion optimization. M. Lopez-Ibanez, L. Paquete, and T. Stuetzle (2010) <doi:10.1007/978-3-642-02538-9_9>.

Version: 1.9-1
Depends: R (≥ 2.10.0)
Imports: modeltools, graphics, grDevices, stats
Suggests: testthat
Published: 2020-03-05
Author: Manuel López-Ibáñez ORCID iD [aut, cre], Marco Chiarandini [aut], Carlos Fonseca [aut], Luis Paquete [aut], Thomas Stützle [aut], Mickaël Binois [ctb]
Maintainer: Manuel López-Ibáñez <manuel.lopez-ibanez at manchester.ac.uk>
BugReports: https://github.com/MLopez-Ibanez/eaf/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://lopez-ibanez.eu/eaftools, https://github.com/MLopez-Ibanez/eaf
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: eaf citation info
Materials: README NEWS
CRAN checks: eaf results


Reference manual: eaf.pdf
Package source: eaf_1.9-1.tar.gz
Windows binaries: r-devel: eaf_1.9-1.zip, r-devel-gcc8: eaf_1.9.zip, r-release: eaf_1.9-1.zip, r-oldrel: eaf_1.9-1.zip
OS X binaries: r-release: eaf_1.9-1.tgz, r-oldrel: eaf_1.9-1.tgz
Old sources: eaf archive

Reverse dependencies:

Reverse suggests: ParamHelpers


Please use the canonical form https://CRAN.R-project.org/package=eaf to link to this page.