finiteSampleCorrection {RobLox}

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

M. Kohl (2005). Numerical Contributions to the Asymptotic Theory of Robustness. Dissertation. University of Bayreuth. https://epub.uni-bayreuth.de/id/eprint/839/2/DissMKohl.pdf.

H. Rieder (1994): Robust Asymptotic Statistics. Springer. doi:10.1007/978-1-4684-0624-5

M. Kohl and H.P. Deigner (2010). Preprocessing of gene expression data by optimally robust estimators. BMC Bioinformatics 11, 583. doi:10.1186/1471-2105-11-583.

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")