finiteSampleCorrection: Function to compute finite-sample corrected radii

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

Function to compute finite-sample corrected radii

Description

Given some radius and some sample size the function computes the corresponding finite-sample corrected radius.

Usage

finiteSampleCorrection(r, n, model = "locsc")

Arguments

r	asymptotic radius (non-negative numeric)
n	sample size
model	has to be "locsc" (for location and scale), "loc" (for location) or "sc" (for scale), respectively.

Details

The finite-sample correction is based on empirical results obtained via simulation studies.

Given some radius of a shrinking contamination neighborhood which leads to an asymptotically optimal robust estimator, the finite-sample empirical MSE based on contaminated samples was minimized for this class of asymptotically optimal estimators and the corresponding finite-sample radius determined and saved.

The computation is based on the saved results of these Monte-Carlo simulations.

Value

Finite-sample corrected radius.

Author(s)

Matthias Kohl [e-mail]

References

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

Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.

Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing the Radius. Statistical Methods and Applications 17(1) 13-40. Extended version: http://r-kurs.de/RRlong.pdf

See Also

roblox, rowRoblox, colRoblox

Examples

finiteSampleCorrection(n = 3, r = 0.001, model = "locsc")
finiteSampleCorrection(n = 10, r = 0.02, model = "loc")
finiteSampleCorrection(n = 250, r = 0.15, model = "sc")

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