makeFormulae: Make all possible formula
In adamlilith/statisfactory: Statistical and Geometrical Tools

makeFormulae

R Documentation

Make all possible formula

Usage

makeFormulae(
  formula,
  intercept = TRUE,
  interceptOnly = TRUE,
  linearOnly = TRUE,
  quad = TRUE,
  ia = TRUE,
  verboten = NULL,
  verbotenCombos = NULL,
  minTerms = NULL,
  maxTerms = NULL,
  returnFx = stats::as.formula,
  verbose = FALSE
)

Arguments

`formula`	A `formula` object with just linear terms.
`intercept`	Logical: If `TRUE` (default) then all models include an intercept. If `FALSE` then then formula will specify that regression occurs through the origin (e.g., `y ~ -1 + etc.`)
`interceptOnly`	Logical: If `TRUE` then an intercept-only model is included in final set.
`linearOnly`	Logical: If `TRUE` (default) then models with only linear terms are included in final set (plus other kinds of models if desired).
`quad`	Logical: If `TRUE` (default), then include quadratic terms.
`ia`	Logical: If `TRUE` (default), then include 2-way interaction terms.
`verboten`	Character vector of terms that should not appear in the models. Ignored if `NULL` (default). You can use this argument, for example, to exclude specific interactions (e.g., `'x1:x2'`, but also include the converse, `'x2:x1'`), or power terms (e.g., `'I(x1^2)'`). Note that to ensure proper matching, you need to use a double backslash in front of each parenthesis and caret ((^)) character.} \item{verbotenCombos}{List of lists: Used to specify specific combinations of terms that should not occur together. See Details below. Ignored if `NULL` (default).} \item{minTerms}{Either a positive integer representing the minimum number of terms required to be in a model, or `NULL` (default) in which case the smallest model can have just one term.} \item{maxTerms}{Either a positive integer representing the maximum number of terms allowed to be in a model, or `NULL` (default) in which case there is no practical limit on the number of terms in a model.} \item{returnFx}{Function used to generate the class of the output objects. Sensible functions in include `as.formula` (default) or `as.character`.} \item{verbose}{Logical: If `TRUE` then display progress. Default is `FALSE`.} } { A vector of formulae. } { This functions creates a list of formulae that contain all possible linear, quadratic, and two-way interaction terms from individual terms in an object of class `formula`. The formulae respect marginality conditions (i.e., they will always include lower-order terms if higher-order terms are included in a formula). Note that if there are more than several terms (i.e., >=3) and interactions and/or quadratic terms are desired, then formula generation may take a long time. } { The argument `verbotenCombos` can be used to specify variables or terms that should not occur in the same formula. The argument `verbotenCombos` is composed of a list of lists. Each sublist comprises names of two variables or terms stated as characters followed by two logical values (`TRUE`/`FALSE`). The second variable/term is removed from the model if the first is in the model. If the first logical value is `TRUE` then the second variable/term is removed if the first variable appears alone in the formula (e.g., not in an interaction with another variable). If the first logical value is `FALSE` then the second variable/term is removed if the first variable/term appears in any term (e.g., as an interaction with another term). Examples: `verbotenCombos=list(list('x1', 'x2', TRUE, TRUE))`: Removes `x2` if `x1` occurs in the model as a linear term. `verbotenCombos=list(list('x1', 'x2', FALSE, TRUE))`: Removes the linear term `x2` if `x1` occurrs in any term in the model. `verbotenCombos=list(list('x1', 'x2', TRUE, FALSE))`: Removes any term with `x2` if the linear term `x1` occurrs in the model. `verbotenCombos=list(list('x1', 'x2', FALSE, FALSE))`: Removes any term with `x2` if any term has `x1`. Quadratic terms and interaction terms can also be used, so: `verbotenCombos=list(list('x1', 'x1:x2', TRUE, TRUE))`: Removes `x1:x2` if `x1` were in the model. `verbotenCombos=list(list('x1', 'I(x2^2)', TRUE, TRUE))`: Removes `I(x2^2)` if `x1` occurs in the model. Note that inexact matching can remove terms incorrectly if inexact matches exist between names of terms or variables. For example, if using an inexact match, then `verbotenCombos(list('x1', 'x2', FALSE, FALSE))` will find any term that has an `x1` (e.g., `x11`) and if it exists, remove any term with an `x2` (e.g., `x25`). Note that reciprocally removing predictors makes little sense since, for example `list(list('x1', 'x2', FALSE, FALSE), list('x2', 'x1', FALSE, FALSE))` removes all formulae with `x2` if `x1` appears then tries to find any models with `x2` that have `x1` (of which there will be none after the first set is removed). } { makeFormulae(y ~ x1 + x2 + x3, maxTerms=3) makeFormulae(y ~ x1 + x2 + x3, ia=FALSE, maxTerms=3) verboten <- c('x1:x2', 'I(x1^2)') makeFormulae(y ~ x1 + x2 + x3, verboten=verboten, maxTerms=3) makeFormulae(y ~ x1 + x2 + x3, maxTerms=3) verbotenCombos <- list(list('x1', 'x2', TRUE, TRUE)) makeFormulae(y ~ x1 + x2 + x3, verbotenCombos=verbotenCombos, maxTerms=3) }