gratia (version 0.8.1)

basis: Basis expansions for smooths

Description

Creates a basis expansion from a definition of a smoother using the syntax of mgcv's smooths via mgcv::s()., mgcv::te(), mgcv::ti(), and mgcv::t2(), or from a fitted GAM(M).

Usage

basis(object, ...)
# S3 method for gam
basis(
  object,
  term = NULL,
  data = NULL,
  n = 100,
  n_2d = 50,
  n_3d = 16,
  n_4d = 4,
  partial_match = FALSE,
  ...
)
# S3 method for scam
basis(
  object,
  term = NULL,
  data = NULL,
  n = 100,
  n_2d = 50,
  n_3d = 16,
  n_4d = 4,
  partial_match = FALSE,
  ...
)
# S3 method for gamm
basis(
  object,
  term = NULL,
  data = NULL,
  n = 100,
  n_2d = 50,
  n_3d = 16,
  n_4d = 4,
  partial_match = FALSE,
  ...
)
# S3 method for list
basis(
  object,
  term = NULL,
  data = NULL,
  n = 100,
  n_2d = 50,
  n_3d = 16,
  n_4d = 4,
  partial_match = FALSE,
  ...
)
# S3 method for default
basis(object, data, knots = NULL, constraints = FALSE, at = NULL, ...)

Value

A tibble.

Arguments

object

a smooth specification, the result of a call to one of mgcv::s()., mgcv::te(), mgcv::ti(), or mgcv::t2(), or a fitted GAM(M) model.

...

other arguments passed to mgcv::smoothCon().

term

character; select smooths in a fitted model

data

a data frame containing the variables used in smooth.

n

numeric; the number of points over the range of the covariate at which to evaluate the smooth.

n_2d

numeric; the number of new observations for each dimension of a bivariate smooth. Not currently used; n is used for both dimensions.

n_3d

numeric; the number of new observations to generate for the third dimension of a 3D smooth.

n_4d

numeric; the number of new observations to generate for the dimensions higher than 2 (!) of a kD smooth (k >= 4). For example, if the smooth is a 4D smooth, each of dimensions 3 and 4 will get n_4d new observations.

partial_match

logical; in the case of character select, should select match partially against smooths? If partial_match = TRUE, select must only be a single string, a character vector of length 1.

knots

a list or data frame with named components containing knots locations. Names must match the covariates for which the basis is required. See mgcv::smoothCon().

constraints

logical; should identifiability constraints be applied to the smooth basis. See argument absorb.cons in mgcv::smoothCon().

at

a data frame containing values of the smooth covariate(s) at which the basis should be evaluated.

Author

Gavin L. Simpson

Examples

load_mgcv()
# \dontshow{
op <- options(pillar.sigfig = 3, cli.unicode = FALSE)
# }
df <- data_sim("eg4", n = 400, seed = 42)

bf <- basis(s(x0), data = df)
bf <- basis(s(x2, by = fac, bs = "bs"), data = df, constraints = TRUE)
# \dontshow{
options(op)
# }