Description Usage Arguments Details Value References
Methods for the edaSeed
generic function.
1 | edaSeedUniform(eda, lower, upper)
|
eda |
|
lower |
Lower bounds of the variables of the objective function. |
upper |
Upper bounds of the variables of the objective function. |
Seeding methods create the initial population. The length of the lower
and upper
vectors determine the number of variables of the objective
function. The following seeding methods are implemented.
edaSeedUniform
Sample each variable from a continuous uniform
distribution in the interval determined by lower
and upper
.
The parameter popSize
sets the number of solutions in the population
(default value: 100
). This is the default method of the
edaSeed
generic function.
A matrix with one column for each variable of the objective function and one row for each solution in the population.
Gonzalez-Fernandez Y, Soto M (2014). copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas. Journal of Statistical Software, 58(9), 1-34. http://www.jstatsoft.org/v58/i09/.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.