wridge_solver: Fit B-Splines with weighted penalization over differences of...
In goepp/aspline: Spline Regression with Adaptive Knot Selection

wridge_solver

R Documentation

Fit B-Splines with weighted penalization over differences of parameters

Description

Fit B-Splines with weighted penalization over differences of parameters

Usage

wridge_solver(
  XX_band,
  Xy,
  degree,
  pen,
  w = rep(1, nrow(XX_band) - degree - 1),
  old_par = rep(1, nrow(XX_band)),
  maxiter = 1000,
  tol = 1e-08
)

Arguments

`XX_band`	The matrix X^T X where `X` is the design matrix. This argument is given in the form of a band matrix, i.e., successive columns represent superdiagonals.
`Xy`	The vector of currently estimated points X^T y, where `y` is the y-coordinate of the data.
`degree`	The degree of the B-splines.
`pen`	Positive penalty constant.
`w`	Vector of weights. The case \mathbf w = \mathbf 1 corresponds to fitting P-splines with difference #' order `degree + 1` (see Eilers, P., Marx, B. (1996) Flexible smoothing with B-splines and penalties.)
`old_par`	Initial parameter to serve as starting point of the iterating process.
`maxiter`	Maximum number of Newton-Raphson iterations to be computed.
`tol`	The tolerance chosen to diagnostic convergence of the adaptive ridge procedure.