FunctionalTerm

Specification for a functional covariate.

Usage

Source

FunctionalTerm(
    name,
    basis="bspline",
    domain=(0.0, 1.0),
    n_basis=15,
    penalty_order=2,
)

Describes how one functional (curve-valued) predictor should enter a FunctionalGAM: which basis to expand its coefficient function beta(t) in, over what domain, at what resolution, and with what roughness penalty.

Attributes

name: str

Name of the functional covariate in the data dict. The corresponding data entry should be a 2-D array of shape (n, T) where T is the number of grid points.

basis: str

Basis type for expanding beta(t): "bspline" (default), a B-spline basis with a difference penalty, or "fourier", a sine/cosine basis with a penalty on higher frequencies.

domain: tuple[float, float]

Tuple (t_min, t_max) specifying the domain of the functional argument. Grid points are assumed equally spaced over this domain.

n_basis: int

Number of basis functions used to represent beta(t). Defaults to 15. Must be >= 3.

penalty_order: int

Order of the difference penalty (for B-spline) or derivative penalty (for Fourier), controlling how strongly higher-order wiggliness in beta(t) is penalized. Defaults to 2 (penalizes curvature).