Title: Important Concepts of Evolutionary Game Theory
Authors@R: c(person("Daniel", "Gebele", role = c("aut", "cph"),
person("Jochen", "Staudacher", role = c("aut","cre", "cph"),
Description: A comprehensive set of tools to illustrate the
core concepts of evolutionary game theory, such as
evolutionary stability or various evolutionary dynamics,
Packaged: 2017-11-26 22:49:02 UTC; jhstaudacher

Description: Evolutionary game theory applies game theory to evolving populations
in biology, see e.g. one of the books by Weibull (1994, ISBN:978-0262731218)
or by Sandholm (2010, ISBN:978-0262195874) for more details. A comprehensive
set of tools to illustrate the core concepts of evolutionary game theory,
such as evolutionary stability or various evolutionary dynamics, for teaching
Packaged: 2022-04-11 04:02:46 UTC; jhstaudacher

Packaged: 2022-08-28 23:21:59 UTC; jhstaudacher

Author: Juan Manuel Cabrera, Federico Giri
Maintainer: Juan Manuel Cabrera <juanmanuelcabrera1@gmail.com>
Imports: ggplot2, reshape2, geomorph, stringr
Description: Evolutionary process simulation using geometric morphometric data. Manipulation of landmark data files (TPS), shape plotting and distances plotting functions.

person("Selahattin", "Guris", email = "sguris@marmara.edu.tr", role = "aut"),
person("Ebru", "Caglayan Akay", email = "winston@rstudio.com", role = "aut"),
person("Burak", "Guris", email = "bguris@istanbul.edu.tr", role = "cre"))
Description: Function and data sets in the book entitled "R ile Temel Ekonometri", S.Guris, E.C.Akay, B. Guris(2020). The book published in Turkish. It is possible to makes Durbin two stage method for autocorrelation, generalized differencing method for correction autocorrelation, Hausman Test for identification and computes LM, LR and Wald test statistics for redundant variable by using the functions written in this package.

Title: Quantile Maximization Likelihood Estimation and Bayesian
Description: Presents two methods to estimate the parameters 'mu', 'sigma', and 'tau' of an ex-Gaussian distribution. Those methods are Quantile Maximization Likelihood Estimation ('QMLE') and Bayesian. The 'QMLE' method allows a choice between three different estimation algorithms for these parameters : 'neldermead' ('NEMD'), 'fminsearch' ('FMIN'), and 'nlminb' ('NLMI'). For more details about the methods you can refer at the following list: Brown, S., & Heathcote, A. (2003) <doi:10.3758/BF03195527>; McCormack, P. D., & Wright, N. M. (1964) <doi:10.1037/h0083285>; Van Zandt, T. (2000) <doi:10.3758/BF03214357>; El Haj, A., Slaoui, Y., Solier, C., & Perret, C. (2021) <doi:10.19139/soic-2310-5070-1251>; Gilks, W. R., Best, N. G., & Tan, K. K. C. (1995) <doi:10.2307/2986138>.
Imports: pracma, stats, nloptr, invgamma, HI, fitdistrplus, gamlss.dist
Author: Yousri SLAOUI [aut, cre] (<https://orcid.org/0000-0001-5295-3311>),