ibr (version 2.0-2)

fittedA: 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.

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.

Details

See the reference for detailed explanation of A and D.

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.

See Also

ibr