Imports: Rcpp (>= 0.12.2), Rsolnp, MASS, xts, numDeriv, zoo, cubature

as described in Ardia et al. (2019) <doi:10.18637/jss.v088.i06>.

Authors@R: c(person("Leopoldo", "Catania", role = c("aut", "cre"),
person("David", "Ardia", role = c("ctb"),
person("Kris", "Boudt", role = c("ctb"),
Author: Leopoldo Catania [aut, cre] (<https://orcid.org/0000-0002-1000-5142>),

Title: Abbreviating Questionnaires (or Other Measures) Using Genetic
Description: The GAabbreviate uses Genetic Algorithms as an optimization tool to create abbreviated forms of lengthy questionnaires (or other measures) that maximally capture the variance in the original data of the long form of the measure.
Authors@R: c(person("Luca", "Scrucca", role = "aut"),
person("Baljinder K.", "Sahdra", role = c("aut", "cre"),
Maintainer: Baljinder K. Sahdra <baljinder.sahdra@acu.edu.au>

Title: Abbreviating Items Measures using Genetic Algorithms
Description: The GAabbreviate package uses Genetic Algorithms as an optimization tool for scale abbreviation or subset selection that maximally captures the variance in the original data.
Authors@R: c(person("Luca", "Scrucca", role = c("aut"),

Description: Scale abbreviation using Genetic Algorithms that maximally capture the variance in the original data.

Title: Searching Parsimony Models with Genetic Algorithms
Authors@R: person("F.J.", "Martinez-de-Pison", email = "fjmartin@unirioja.es", role = c("aut", "cre"))
Description: Methodology that combines feature selection, model tuning, and parsimonious model selection with Genetic Algorithms (GA) proposed in {Martinez-de-Pison} (2015) <DOI:10.1016/j.asoc.2015.06.012>. To this objective, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.
Suggests: parallel, doParallel, doRNG (>= 1.6), knitr (>= 1.8), lhs,
MASS, caret, mlbench, e1071, nnet, kernlab
Author: F.J. Martinez-de-Pison [aut, cre]

Title: Generalized Beta Distribution of the Second Kind: properties,
Author: Monique Graf <monique.graf@bfs.admin.ch>, Desislava Nedyalkova
Description: GB2 is a simple package that calculates the basic
properties of the Generalized Beta distribution of the second
kind - density, distribution function, quantiles, moments.
Functions for the full loglikelihood, the profile loglikelihood
and the scores are provided. Formulae for various Laeken
indicators under the GB2 are implemented. It performs maximum
likelihood estimation and non-linear least squares eastimation
of the model parameters. It provides various polots for the
vizualization and analysis of the results.
Imports: hypergeo, laeken, numDeriv, stats