as.basis.formula: Convert Formula or Factor to Basis Function

In basefun: Infrastructure for Computing with Basis Functions

Convert Formula or Factor to Basis Function

Description

Convert a formula or factor to basis functions

Usage

as.basis(object, ...)
## S3 method for class 'formula'
as.basis(object, data = NULL, remove_intercept = FALSE, 
         ui = NULL, ci = NULL, negative = FALSE, scale = FALSE, 
         Matrix = FALSE, prefix = "", drop.unused.levels = TRUE, ...)
## S3 method for class 'factor_var'
as.basis(object, ...)
## S3 method for class 'ordered_var'
as.basis(object, ...)
## S3 method for class 'factor'
as.basis(object, ...)
## S3 method for class 'ordered'
as.basis(object, ...)

Arguments

object	a formula or an object of class factor, factor_var, ordered or ordered_var
data	either a vars object or a data.frame
remove_intercept	a logical indicating if any intercept term shall be removed
ui	a matrix defining constraints
ci	a vector defining constraints
negative	a logical indicating negative basis functions
scale	a logical indicating a scaling of each column of the model matrix to the unit interval (based on observations in data)
Matrix	a logical requesting a sparse model matrix, that is, a Matrix object.
prefix	character prefix for model matrix column names (allows disambiguation of parameter names).
drop.unused.levels	logical, should factors have unused levels dropped?
...	additional arguments to model.matrix, for example contrasts

Details

as.basis returns a function for the evaluation of the basis functions with corresponding model.matrix and predict methods.

Unordered factors (classes factor and factor_var) use a dummy coding and ordered factor (classes ordered or ordered_var) lead to a treatment contrast to the last level and removal of the intercept term with monotonicity constraint. Additional arguments (...) are ignored for ordered factors.

Linear constraints on parameters parm are defined by ui %*% parm >= ci.

Examples

  ## define variables and basis functions
  v <- c(numeric_var("x"), factor_var("y", levels = LETTERS[1:3]))
  fb <- as.basis(~ x + y, data = v, remove_intercept = TRUE, negative = TRUE,
                 contrasts.arg = list(y = "contr.sum"))

  ## evaluate basis functions
  model.matrix(fb, data = as.data.frame(v, n = 10))
  ## basically the same as (but wo intercept and times -1)
  model.matrix(~ x + y, data = as.data.frame(v, n = 10))

  ### factor
  xf <- gl(3, 1)
  model.matrix(as.basis(xf), data = data.frame(xf = xf))

  ### ordered
  xf <- gl(3, 1, ordered = TRUE)
  model.matrix(as.basis(xf), data = data.frame(xf = unique(xf)))

basefun documentation built on Oct. 3, 2025, 3 p.m.