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

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

Description

The function rlsOptIC.AnMad computes the optimally robust IC for AnMad estimators in case of normal location with unknown scale and (convex) contamination neighborhoods. These estimators were considered in Andrews et al. (1972). A definition of these estimators can also be found in Subsection 8.5.3 of Kohl (2005).

Usage

rlsOptIC.AnMad(r, aUp = 2.5, delta = 1e-06)

Arguments

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

Details

The optimal value of the tuning constant a can be read off from the slot Infos of the resulting IC.

Value

Object of class "IC"

Author(s)

Matthias Kohl [e-mail]

References

Andrews, D.F., Bickel, P.J., Hampel, F.R., Huber, P.J., Rogers, W.H. and Tukey, J.W. (1972) Robust estimates of location. Princeton University Press.

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

See Also

IC-class

Examples

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

RobLox documentation built on May 2, 2019, 11:03 a.m.