R: Setting up initial candidate models

initial {AVGAS}

R Documentation

Setting up initial candidate models

Description

This function automatically ranks all candidate interaction effects under Strong, Weak, or No heredity condition and obtains initial candidate models.

Usage

initial(
  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. This number can be different from the `r1` defined in `detect`.
`r2`	A numeric value indicating the maximum number of interaction effects. This number can be different from the `r2` defined in `detect`.
`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:

`initialize`	Initial candidate models. A numeric matrix of dimension `q` by `r1+r2` where each row represents a fitted model. Duplicated models are allowed.
`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`.

Examples

# Under Strong heredity