This function tries to provide a rough approximation to
best solution when no information is available for the correct range
of input parameters for the objective function. It can useful for
studying the behavior of individual-based models with high
variability in the output variables showing nonlinear behaviors.
Usage
abm.ees1(objective, options = NULL)
Arguments
objective
An instance of ObjectiveFunction (or subclass) class ObjectiveFunction
options
An apropiate instance from a sublclass of Options class
# NOT RUN { f<- PlainFunction$new(f0.rosenbrock2)
f$Parameter(name="x1",min=-100,max=100)
f$Parameter(name="x2",min=-100,max=100)
extremize("ees1", f)
# }# NOT RUN {# }