rlsOptIC.Hu1: Computation of the optimally robust IC for Hu1 estimators

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

Computation of the optimally robust IC for Hu1 estimators

Description

The function rlsOptIC.Hu1 computes the optimally robust IC for Hu1 estimators in case of normal location with unknown scale and (convex) contamination neighborhoods. These estimators were proposed by Huber (1964), Proposal 2. A definition of these estimators can also be found in Subsection 8.5.1 of Kohl (2005).

Usage

rlsOptIC.Hu1(r, kUp = 2.5, delta = 1e-06)

Arguments

r	non-negative real: neighborhood radius.
kUp	positive real: the upper end point of the interval to be searched for k.
delta	the desired accuracy (convergence tolerance).

Details

The optimal value of the tuning constant 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

Huber, P.J. (1964) Robust estimation of a location parameter. Ann. Math. Stat. 35: 73–101.

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

See Also

IC-class

Examples

IC1 <- rlsOptIC.Hu1(r = 0.1)
checkIC(IC1)
Risks(IC1)
Infos(IC1)
plot(IC1)
infoPlot(IC1)

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