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
 [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 |