betaS1lr {ibr} | R Documentation |
Coefficients for iterative bias reduction method.
Description
The function evaluates the smoothing matrix H
, the
matrices Q and S and their associated
coefficients c
and s
. This function is not intended to be used directly.
Usage
betaS1lr(n,U,tUy,eigenvaluesS1,ddlmini,k,lambda,rank,Rm1U,index0)
Arguments
n |
The number of observations. |
U |
The the matrix of eigen vectors of the symmetric smoothing matrix S. |
tUy |
The transpose of the matrix of eigen vectors of the symmetric smoothing matrix S times the vector of observation y. |
eigenvaluesS1 |
Vector of the eigenvalues of the symmetric smoothing matrix S. |
ddlmini |
The number of eigen values of S equal to 1. |
k |
A numeric vector which give the number of iterations. |
lambda |
The smoothness coefficient lambda for thin plate splines of
order |
rank |
The rank of lowrank splines. |
Rm1U |
matrix R^-1U (see reference). |
index0 |
The index of the first eigen values of S numerically equal to 0. |
Details
See the reference for detailed explanation of Q (the semi kernel or radial basis) and S (the polynomial null space).
Value
Returns beta
Author(s)
Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober
References
Wood, S.N. (2003) Thin plate regression splines. J. R. Statist. Soc. B, 65, 95-114.