iterchoiceS1e: Number of iterations selection for iterative bias reduction...

Description Usage Arguments Value Author(s) References See Also

Description

Evaluate at each iteration proposed in the grid the value of different criteria: GCV, AIC, corrected AIC, BIC and gMDL (along with the ddl and sigma squared). The minimum of these criteria gives an estimate of the optimal number of iterations. This function is not intended to be used directly.

Usage

1
iterchoiceS1e(y, K, tUy, eigenvaluesS1, ddlmini, ddlmaxi)

Arguments

y

The response variable

K

A numeric vector which give the search grid for iterations

eigenvaluesS1

Vector of the eigenvalues of the symmetric smoothing matrix S.

tUy

The transpose of the matrix of eigen vectors of the symmetric smoothing matrix S times the vector of observation y.

ddlmini

The number of eigen values of S equal to 1.

ddlmaxi

The maximum df. No criteria are calculated beyond the number of iterations that leads to df bigger than this bound.

Value

Returns the values of GCV, AIC, corrected AIC, BIC, gMDL, df and sigma squared for each value of the grid K. Inf are returned if the iteration leads to a smoother with a df bigger than ddlmaxi.

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, iterchoiceS1


ibr documentation built on May 2, 2019, 8:22 a.m.