Penalty.matrix: Penalty matrix for higher order differences

In ppls: Penalized Partial Least Squares

Description

This function computes the matrix that penalizes the higher order differences.

Usage

Penalty.matrix(m,order = 2)

Arguments

m	vector. The jth entry determines the size of the jth block in the penalty term.
order	order of the differences. Default value is order=2.

Details

For the jth entry of the vector m, and for the default values order=2, the penalty matrix P_j penalizes the second order differences of a vector v of length m[j]. That is

v^T P_j v= ∑_{i=3} ^{m[j]} (Δ v_i) ^2

where

Δ v_i= v_i -2 v_{i-1} + v_{i-2}

is the second order difference. This definition is easily extended to other values of order. The final penalty matrix P is a block-diagonal matrix with the jth block equal to P_j. More details can be found in Kraemer, Boulesteix, and Tutz (2008).

Value

penalty matrix of size sum(m) x sum(m)

Warning

All entries of the vector m must be larger than order, as the notion of kth order differences does not make sense for vectors of length ≤ k.

Author(s)

Nicole Kraemer

References

N. Kraemer, A.-L. Boulsteix, and G. Tutz (2008). Penalized Partial Least Squares with Applications to B-Spline Transformations and Functional Data. Chemometrics and Intelligent Laboratory Systems, 94, 60 - 69. http://dx.doi.org/10.1016/j.chemolab.2008.06.009

C. de Boor (1978) A Practical Guide to Splines, Springer.

See Also

penalized.pls

Examples

 P<-Penalty.matrix(c(6,4),2)
# a more detailed example can be found under penalized.pls()

Example output

Loading required package: splines
Loading required package: MASS

ppls documentation built on May 1, 2019, 10:53 p.m.