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rlsOptIC.Tu2

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)

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

Examples

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

RobLox

Optimally Robust Influence Curves and Estimators for Location and Scale

v1.2.0
LGPL-3
Authors
Matthias Kohl [cre, cph], Peter Ruckdeschel [aut, cph]
Initial release
2019-04-02

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