fittedS1lr: Evaluate the fit for iterative bias reduction model

Description Usage Arguments Details Value Author(s) References See Also

Description

The function evaluates the fit for iterative bias reduction model for iteration k. This function is not intended to be used directly.

Usage

1
fittedS1lr(n,U,tUy,eigenvaluesS1,ddlmini,k,rank)

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 gives the number of iterations

rank

The rank of lowrank splines.

Details

see the reference for detailed explanation of computation of iterative bias reduction smoother

Value

Returns a vector containing the fit

Author(s)

Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober

References

Cornillon, P.-A.; Hengartner, N.; Jegou, N. and Matzner-Lober, E. (2012) Iterative bias reduction: a comparative study. Statistics and Computing, 23, 777-791.

Cornillon, P.-A.; Hengartner, N. and Matzner-Lober, E. (2013) Recursive bias estimation for multivariate regression smoothers Recursive bias estimation for multivariate regression smoothers. ESAIM: Probability and Statistics, 18, 483-502.

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

See Also

ibr



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