betaA: Calculates coefficients for iterative bias reduction...

In ibr: Iterative Bias Reduction

Calculates coefficients for iterative bias reduction smoothers

Description

Calculates the coefficients for the iterative bias reduction smoothers. This function is not intended to be used directly.

Usage

betaA(n, eigenvaluesA, tPADmdemiY, DdemiPA, ddlmini, k, index0)

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.
index0	The index of the first eigen values of S numerically equal to 0.

Details

See the reference for detailed explanation of A and D and the meaning of coefficients.

Value

Returns the vector of coefficients (of length n, the number of observations.)

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.