betaA: Calculates coefficients for iterative bias reduction...

Description Usage Arguments Details Value Author(s) References See Also

Description

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

Usage

1
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 May 2, 2019, 8:22 a.m.