| fittedS1lr {ibr} | R Documentation |
Evaluate the fit for iterative bias reduction model
Description
The function evaluates the fit for iterative bias reduction
model for iteration k. This function is not intended to be used directly.
Usage
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.
Cornillon, P.-A.; Hengartner, N. and Matzner-Lober, E. (2017) Iterative Bias Reduction Multivariate Smoothing in R: The ibr Package. Journal of Statistical Software, 77, 1–26.
Wood, S.N. (2003) Thin plate regression splines. J. R. Statist. Soc. B, 65, 95-114.