Easy.Calibration: Easy.Calibration
Description
Search for the best set of parameters trying to
minimize the calibration function provided by the user. The function
has to operational models, the first based on the experimental setup
where all parameters are defined a priori and the second using
optimization techniques. Currently the only supported optimization
technique is the particle swarm optimization.Usage
Easy.Calibration(m.dir, m.ds, m.time = 300, parameters, exp.n = 100,
exp.r = 1, FUN)
Arguments
m.dir
The installation directory of some repast model
m.ds
The name of any model aggregate dataset
m.time
The total simulated time
parameters
-- The input factors
exp.n
-- The experiment sample size
exp.r
-- The number of experiment replications
FUN
-- THe calibration function.
Value
- A list with holding experimnt, object and charts
References
[1] Poli, R., Kennedy, J., & Blackwell, T. (2007). Particle swarm optimization.
Swarm Intelligence, 1(1), 33-57.