wridge_solver {aspline}

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.

Value

The estimated parameter of the spline regression.