ibr (version 1.4.5)

iterchoiceAcve: Selection of the number of iterations for iterative bias reduction smoothers

Description

Evaluates at each iteration proposed in the grid the cross-validated root mean squared error (RMSE) and mean of the relative absolute error (MAP). The minimum of these criteria gives an estimate of the optimal number of iterations. This function is not intended to be used directly.

Usage

iterchoiceAcve(X, y, bx, df, kernelx, ddlmini, ntest, ntrain,
Kfold, type, npermut, seed, Kmin, Kmax)

Value

Returns the values of RMSE and MAP for each value of the grid K. Inf are returned if the iteration leads to a smoother with a df bigger than ddlmaxi.

References

Cornillon, P.-A.; Hengartner, N.; Jegou, N. and Matzner-Lober, E. (2012) Iterative bias reduction: a comparative study. Statistics and Computing. Doi: 10.1007/s11222-012-9346-4

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. Doi: http://dx.doi.org/10.1051/ps/2013046

See Also

ibr