Functional Basis Regression — fregre.basis • fdars

Fits a functional linear model using basis expansion (ridge regression). Uses the anofox-regression Rust backend for efficient L2-regularized regression.

Usage

fregre.basis(fdataobj, y, basis.x = NULL, basis.b = NULL, lambda = 0, ...)

Arguments

fdataobj: An object of class 'fdata' (functional covariate).
y: Response vector.
basis.x: Basis for the functional covariate (currently ignored).
basis.b: Basis for the coefficient function (currently ignored).
lambda: Smoothing/regularization parameter (L2 penalty).
...: Additional arguments.

Value

A fitted regression object of class 'fregre.fd' with components:

coefficients: Beta coefficient function values
intercept: Intercept term
fitted.values: Fitted values
residuals: Residuals
lambda: Regularization parameter used
r.squared: R-squared (coefficient of determination)
mean.X: Mean of functional covariate (for prediction)
mean.y: Mean of response (for prediction)
sr2: Residual variance
fdataobj: Original functional data
y: Response vector
call: The function call