Packaged: Mon May  5 21:30:50 2008; verzani

Title: Gadget is the Globally-Applicable Area Disaggregated General
Authors@R: c(person("Bjarki Thor", "Elvarsson", email="bjarki.elvarsson@hafogvatn.is",role = c("aut", "cre")),
person("Jamie", "Lentin", email="lentinj@shuttlethread.com",role = c("ctb")),
person("Morten Nygard","Asnes", role = c("ctb")),
person("Audbjorg","Jakobsdottir", role = c("ctb") ),
person("Gudmundur", "Einarsson", role = c("ctb")),
person("Kristjana Yr", "Jonsdottir", role = c("ctb")),
person("Mark G.","Johnson", role = c("ctb","cph")),
person("Marine and Freshwater Research Institute (Iceland)", role = c("cph")))
Maintainer: Bjarki Thor Elvarsson <bjarki.elvarsson@hafogvatn.is>
Description: A statistical ecosystem modelling package, taking many features of
the ecosystem into account. Gadget works by running an internal
model based on many parameters, and then comparing the data from
the output of this model to real data to get a goodness-of-fit
likelihood score. These parameters can then be adjusted, and the
model re-run, until an optimum is found, which corresponds to the
model with the lowest likelihood score. Gadget allows the user to
include a number of features into an ecosystem model: One or more
species, each of which may be split into multiple stocks; multiple
areas with migration between areas; predation between and within
species; maturation; reproduction and recruitment; multiple
commercial and survey fleets taking catches from the populations.
For more details see <https://hafro.github.io/gadget2>.
This is the C++ Gadget2 runtime, making it available for R.
Author: Bjarki Thor Elvarsson [aut, cre],
Marine and Freshwater Research Institute (Iceland) [cph]

For more details see <https://hafro.github.io/gadget2/>.

For more details see <https://gadget-framework.github.io/gadget2/>.

Title: Genetic Algorithm for Curve Fitting
Description: A group of sample points are evaluted against a user-defined expression,
the sample points are lists of parameters with values that may be substituted into
that expression. The genetic algorithm attmepts to make the result of the expression
as low as possible (usually this would be a squares of residuals value).