Title: Individual Based Model Population Simulation
person('Daphné', 'Giorgi', role = c('aut', 'cre'),
person('Vincent', 'Lemaire', role = 'aut',
Description: Simulation of the random evolution of structured population dynamics, called stochastic Individual Based Models (IBMs) (see e.g. Ferrière and Tran (2009) <doi:10.1051/proc/2009033>, Bansaye and Méléard (2015) <doi:10.1007/978-3-319-21711-6>, Boumezoued (2016)).
The package allows users to simulate the random evolution of a population in which individuals are characterised by their date of birth, a set of attributes, and their potential date of death.
Imports: Rcpp (>= 0.12), checkmate, stats, utils, readr, rlang, tidyr,
dplyr (>= 0.8.0), reshape, purrr, ggplot2
Suggests: RcppArmadillo, knitr, rmarkdown, bookdown, ggfortify, magick,

Title: R API to Interactive Brokers Trader Workstation
Description: Provides native Raccess to Interactive Brokers Trader Workstation API.
Packaged: Thu Feb 21 16:10:07 2008; jryan

Packaged: Tue May  6 09:21:23 2008; hornik

Packaged: Mon Nov 17 15:05:05 2008; jryan

Maintainer: Joshua M. Ulrich <josh.m.ulrich@gmail.com>
Description: Provides native R access to Interactive Brokers Trader Workstation API.

Description: Provides native Raccess to Interactive Brokers Trader
Packaged: Mon May 11 12:44:59 2009; jryan

Packaged: Wed May 13 00:13:12 2009; jryan

Description: Provides native R access to Interactive Brokers Trader

Title: Inequality and Concentration Indices and Curves
Description: Lorenz and concentration curves; Atkinson, Generalized
entropy and SGini indices (with decomposition)
Packaged: 2012-08-09 16:21:31 UTC; didier.plat

Author: Farimah Houshmand, Farzad Eskandari Ph.D. <Askandari@atu.ac.ir>
Description: Imperialist Competitive Algorithm (ICA)
is a computational method that is used to solve optimization
problems of different types and it is the mathematical model
and the computer simulation of human social evolution.
The package provides a minimum value for the cost function
and the best value for the optimization variables by
Users can easily define their own objective function
This version has been successfully applied to solve
optimization problems, for continuous functions.