rlsOptIC.Tu2: Computation of the optimally robust IC for Tu2 estimators

In RobLox: Optimally Robust Influence Curves and Estimators for Location and Scale

Computation of the optimally robust IC for Tu2 estimators

Description

The function rlsOptIC.Tu2 computes the optimally robust IC for Tu2 estimators in case of normal location with unknown scale and (convex) contamination neighborhoods. The definition of these estimators can be found in Subsection 8.5.4 of Kohl (2005).

Usage

rlsOptIC.Tu2(r, a.start = 5, k.start = 1.5, delta = 1e-06, MAX = 100)

Arguments

r	non-negative real: neighborhood radius.
a.start	positive real: starting value for a.
k.start	positive real: starting value for k.
delta	the desired accuracy (convergence tolerance).
MAX	if a or k are beyond the admitted values, MAX is returned.

Details

The computation of the optimally robust IC for Tu2 estimators is based on optim where MAX is used to control the constraints on a and k. The optimal values of the tuning constant a and k can be read off from the slot Infos of the resulting IC.

Value

Object of class "IC"

Author(s)

Matthias Kohl [e-mail]

References

Beaton, A.E. and Tukey, J.W. (1974) The fitting of power series, meaning polynomials, illustrated on band-spectroscopic data. Discussions. Technometrics 16: 147–185.

Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.

See Also

IC-class

Examples

IC1 <- rlsOptIC.Tu2(r = 0.1)
checkIC(IC1)
Risks(IC1)
Infos(IC1)
plot(IC1)
infoPlot(IC1)

RobLox documentation built on Feb. 4, 2024, 3 p.m.