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).
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, ...)
A tibble.
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()
.
character; select smooths in a fitted model
a data frame containing the variables used in smooth
.
numeric; the number of points over the range of the covariate at which to evaluate the smooth.
numeric; the number of new observations for each dimension of a
bivariate smooth. Not currently used; n
is used for both dimensions.
numeric; the number of new observations to generate for the third dimension of a 3D smooth.
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.
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.
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()
.
logical; should identifiability constraints be applied to
the smooth basis. See argument absorb.cons
in mgcv::smoothCon()
.
a data frame containing values of the smooth covariate(s) at which the basis should be evaluated.
Gavin L. Simpson
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)
# }
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