fittedA: Evaluates the fits for iterative bias reduction method

In ibr: Iterative Bias Reduction

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.

See Also

ibr

ibr documentation built on Sept. 13, 2023, 5:08 p.m.