Build a list of basis functions from a set of columns
basis_list_cols(
cols,
x,
smoothness_orders,
include_zero_order,
include_lower_order = FALSE
)Index or indices (as numeric) of covariates (columns) of
interest in the data matrix x for which basis functions ought to be
generated. Note that basis functions for interactions of these columns are
computed automatically.
A matrix containing observations in the rows and covariates
in the columns. Basis functions are computed for these covariates.
An integer vector of length ncol(x)
specifying the desired smoothness of the function in each covariate. k = 0
is no smoothness (indicator basis), k = 1 is first order smoothness, and so
on. For an additive model, the component function for each covariate will
have the degree of smoothness as specified by smoothness_orders. For
non-additive components (tensor products of univariate basis functions),
the univariate basis functions in each tensor product have smoothness
degree as specified by smoothness_orders.
A logical, indicating whether the zeroth
order basis functions are included for each covariate (if TRUE), in
addition to the smooth basis functions given by smoothness_orders.
This allows the algorithm to data-adaptively choose the appropriate degree
of smoothness.
A logical, like include_zero_order,
except including all basis functions of lower smoothness degrees than
specified via smoothness_orders.
A list containing the basis functions generated from a set of
input columns.