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. and Matzner-Lober, E. (2009) Recursive Bias Estimation for high dimensional regression smoothers. submitted.

See Also

ibr


[Package ibr version 1.2 Index]