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,
select = NULL,
term = deprecated(),
data = NULL,
n = 100,
n_2d = 50,
n_3d = 16,
n_4d = 4,
partial_match = FALSE,
...
)
# S3 method for scam
basis(
object,
select = NULL,
term = deprecated(),
data = NULL,
n = 100,
n_2d = 50,
n_3d = 16,
n_4d = 4,
partial_match = FALSE,
...
)
# S3 method for gamm
basis(
object,
select = NULL,
term = deprecated(),
data = NULL,
n = 100,
n_2d = 50,
n_3d = 16,
n_4d = 4,
partial_match = FALSE,
...
)
# S3 method for list
basis(
object,
select = NULL,
term = deprecated(),
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, ...)
Arguments
- object
a smooth specification, the result of a call to one of
mgcv::s()
.,mgcv::te()
,mgcv::ti()
, ormgcv::t2()
, or a fitted GAM(M) model.- ...
other arguments passed to
mgcv::smoothCon()
.- select
character; select smooths in a fitted model
- term
- 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
, shouldselect
match partially againstsmooths
? Ifpartial_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
inmgcv::smoothCon()
.- at
a data frame containing values of the smooth covariate(s) at which the basis should be evaluated.