Description: Compute a matrix comparison of lists (from 2 to infinite) and plot the results in a Venn diagram if (N<=4) with regulation details. It allows to produce a complete annotated file, merging the annotations of the compared lists. It is also possible to compute an overlaps table to show the overlaps proportions of all the couples of lists and draw proportional Venn diagrams.

Title: Fitting Dose-Response Models Using an Evolutionary Algorithm
Description: Fits dose-response models using an evolutionary
algorithm to estimate the model parameters. The procedure currently
can fit 3-parameter, 4-parameter, and 5-parameter log-logistic models
as well as exponential models. Functions are also provided to plot,
make predictions, and calculate confidence intervals for the resulting
models. For details see "Nonlinear Dose-response Modeling of
High-Throughput Screening Data Using an Evolutionary Algorithm",
Ma, J., Bair, E., Motsinger-Reif, A.; Dose-Response (In press).

Ma, J., Bair, E., Motsinger-Reif, A.; Dose-Response

Title: Plots of the Empirical Attainment Function
Author: Carlos Fonseca, Luis Paquete, Thomas Stützle, Manuel
Description: Plots of the empirical attainment function for two

Author: Carlos Fonseca, Luis Paquete, Thomas Stützle, Manuel López-Ibáñez and Marco Chiarandini.
Description: Plots of the empirical attainment function for two objectives.

Authors@R: c(person("Manuel", "López-Ibáñez", role = c("aut", "cre"),
person("Marco", "Chiarandini", role = "aut"),
person("Carlos", "Fonseca", role = "aut"),
person("Luis", "Paquete", role = "aut"),
person("Thomas", "Stützle", role = "aut"))
Imports: modeltools, graphics, grDevices, stats

person("Thomas", "Stützle", role = "aut"),
person("Mickaël", "Binois", role = "ctb"))
Description: 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>.

person("Luís", "Paquete", role = "aut"),
Description: 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>.
Imports: modeltools, graphics, grDevices, stats, Rdpack
SystemRequirements: GNU make, Gnu Scientific Library