smooth.construct.pss.smooth.spec: P-spline constructor with modified 'shrinkage' penalty

In refund: Regression with Functional Data

P-spline constructor with modified 'shrinkage' penalty

Description

Construct a B-spline basis with a modified difference penalty of full rank (i.e., that also penalizes low-order polynomials).

Usage

## S3 method for class 'pss.smooth.spec'
smooth.construct(object, data, knots)

Arguments

object	see smooth.construct. The shrinkage factor can be specified via object$xt$shrink
data	see smooth.construct.
knots	see smooth.construct.

Details

This penalty-basis combination is useful to avoid non-identifiability issues for ff terms. See 'ts' or 'cs' in smooth.terms for similar "shrinkage penalties" for thin plate and cubic regression splines. The basic idea is to replace the k-th zero eigenvalue of the original penalty by s^k \nu_m, where s is the shrinkage factor (defaults to 0.1) and \nu_m is the smallest non-zero eigenvalue. See reference for the original idea, implementation follows that in the 'ts' and 'cs' constructors (see smooth.terms).

Author(s)

Fabian Scheipl; adapted from 'ts' and 'cs' constructors by S.N. Wood.

References

Marra, G., & Wood, S. N. (2011). Practical variable selection for generalized additive models. Computational Statistics & Data Analysis, 55(7), 2372-2387.

refund documentation built on Nov. 14, 2023, 5:07 p.m.