cross {AVGAS} | R Documentation |
Performing crossover
Description
This function performs crossover which only stores all fitted models without making any comparison. The selected indices in each fitted model will be automatically re-ordered so that main effects comes first, followed by two-way interaction effects, and zero reservation spaces.
Usage
cross(parents, heredity = "Strong", nmain.p, r1, r2, interaction.ind = NULL)
Arguments
parents |
A numeric matrix of dimension |
heredity |
Whether to enforce Strong, Weak, or No heredity. Default is "Strong". |
nmain.p |
A numeric value that represents the total number of main effects
in |
r1 |
A numeric value indicating the maximum number of main effects. |
r2 |
A numeric value indicating the maximum number of interaction effects. |
interaction.ind |
A two-column numeric matrix containing all possible
two-way interaction effects. It must be generated outside of this function
using |
Value
A numeric matrix single.child.bit
is returned. Each row representing
a fitted model, and each column corresponding to the predictor index in the fitted model.
Duplicated models are allowed.
See Also
Examples
# Under Strong heredity
set.seed(0)
nmain.p <- 4
interaction.ind <- t(combn(4,2))
X <- matrix(rnorm(50*4,1,0.1), 50, 4)
epl <- rnorm(50,0,0.01)
y<- 1+X[,1]+X[,2]+X[,1]*X[,2]+epl
p1 <- initial(X, y, nmain.p = 4, r1 = 3, r2 = 3,
interaction.ind = interaction.ind, q = 5)
c1 <- cross(p1, nmain.p=4, r1 = 3, r2 = 3,
interaction.ind = interaction.ind)