Computation and visualization of the empirical attainment function (EAF) for the analysis of random sets in multi-criterion optimization. M. López-Ibáñez, L. Paquete, and T. Stützle (2010) <doi:10.1007/978-3-642-02538-9_9>.
| Version: |
2.3 |
| Depends: |
R (≥ 3.2) |
| Imports: |
modeltools, graphics, grDevices, stats, Rdpack |
| Suggests: |
testthat, withr, viridisLite |
| Published: |
2021-12-21 |
| Author: |
Manuel López-Ibáñez
 [aut, cre],
Marco Chiarandini [aut],
Carlos Fonseca [aut],
Luís 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: |
https://mlopez-ibanez.github.io/eaf/,
https://github.com/MLopez-Ibanez/eaf |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make, Gnu Scientific Library |
| Citation: |
eaf citation info |
| Materials: |
README NEWS |
| CRAN checks: |
eaf results |