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ibr (version 2.0-2)

betaS1lr: 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 m.
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.

Value

Returns beta

Details

See the reference for detailed explanation of Q (the semi kernel or radial basis) and S (the polynomial null space).

References

Wood, S.N. (2003) Thin plate regression splines. J. R. Statist. Soc. B, 65, 95-114.

See Also

ibr