| fittedA {ibr} | R Documentation |
Evaluates the fits for iterative bias reduction method
Description
Evaluates the fits for the iterative bias reduction smoother, using a kernel smoother and its decomposition into a symmetric matrix and a diagonal matrix. This function is not intended to be used directly.
Usage
fittedA(n, eigenvaluesA, tPADmdemiY, DdemiPA, ddlmini, k)Arguments
n |
The number of observations. |
eigenvaluesA |
Vector of the eigenvalues of the symmetric matrix A. |
tPADmdemiY |
The transpose of the matrix of eigen vectors of the symmetric matrix A times the inverse of the square root of the diagonal matrix D. |
DdemiPA |
The square root of the diagonal matrix D times the eigen vectors of the symmetric matrix A. |
ddlmini |
The number of eigenvalues (numerically) equals to 1. |
k |
A scalar which gives the number of iterations. |
Details
See the reference for detailed explanation of A and D.
Value
Returns a list of two components: fitted contains fitted values
and trace contains the trace (effective degree of freedom) of the iterated
bias reduction smoother.
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.