detect {AVGAS}

Suggesting values for r2

Description

This function suggests the values for r2.

Usage

detect(
  X,
  y,
  heredity = "Strong",
  nmain.p,
  sigma = NULL,
  r1,
  r2,
  interaction.ind = NULL,
  pi1 = 0.32,
  pi2 = 0.32,
  pi3 = 0.32,
  lambda = 10,
  q = 40
)

Arguments

X

Input data. An optional data frame, or numeric matrix of dimension n by nmain.p. Note that the two-way interaction effects should not be included in X because this function automatically generates the corresponding two-way interaction effects if needed.

y

Response variable. A n-dimensional vector, where n is the number of observations in X.

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 X.

sigma

The standard deviation of the noise term. In practice, sigma is usually unknown. In such case, this function automatically estimate sigma using root mean square error (RMSE). Default is NULL. Otherwise, users need to enter a numeric value.

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 t(utils::combn()). See Example section for details.

pi1

A numeric value between 0 and 1, defined by users. Default is 0.32. For guidance on selecting an appropriate value, please refer to ABC.

pi2

A numeric value between 0 and 1, defined by users. Default is 0.32. For guidance on selecting an appropriate value, please refer to ABC.

pi3

A numeric value between 0 and 1, defined by users. Default is 0.32. For guidance on selecting an appropriate value, please refer to ABC.

lambda

A numeric value defined by users. Default is 10. For guidance on selecting an appropriate value, please refer to ABC.

q

A numeric value indicating the number of models in each generation (e.g., the population size). Default is 40.

Value

A list of output. The components are:

InterRank

Rank of all candidate interaction effects. A two-column numeric matrix. The first column contains indices of ranked two-way interaction effects, and the second column contains its corresponding ABC score.

mainind.sel

Selected main effects. A r1-dimensional vector.

mainpool

Ranked main effects in X.

plot

Plot of potential interaction effects and their corresponding ABC scores.

See Also

initial.

Examples

# under Strong heredity

# under No 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
d2 <- detect(X, y, heredity = "No", nmain.p = 4, r1 = 3, r2 = 3,
    interaction.ind = interaction.ind, q = 5)