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ibr (version 2.0-2)

betaS1: 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

betaS1(n,U,tUy,eigenvaluesS1,ddlmini,k,lambda,Sgu,Qgu,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.
Sgu
The matrix of the polynomial null space S.
Qgu
The matrix of the semi kernel (or radial basis) Q.
index0
The index of the first eigen values of S numerically equal to 0.

Value

Returns a list containing of coefficients for the null space dgub and the semi-kernel cgub

Details

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

References

C. Gu (2002) Smoothing spline anova models. New York: Springer-Verlag.

See Also

ibr