RobLox (version 0.8.2)

RobLox-package: Optimally robust influence curves and estimators for location and scale

Description

Functions for the determination of optimally robust influence curves and estimators in case of normal location and/or scale.

Package versions

Note: The first two numbers of package versions do not necessarily reflect package-individual development, but rather are chosen for the RobAStXXX family as a whole in order to ease updating "depends" information.

Details

ll{ Package: RobLox Version: 0.8.2 Date: 2012-09-12 Depends: R(>= 2.7.0), stats, lattice, RColorBrewer, Biobase, distr, distrMod, RobAStBase Suggests: MASS LazyLoad: yes ByteCompile: yes License: LGPL-3 URL: http://robast.r-forge.r-project.org/ SVNRevision: 519 }

References

M. Kohl (2005). Numerical Contributions to the Asymptotic Theory of Robustness. Dissertation. University of Bayreuth. 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://www.stamats.de/RRlong.pdf M. Kohl, P. Ruckdeschel, and H. Rieder (2010). Infinitesimally Robust Estimation in General Smoothly Parametrized Models. Statistical Methods and Application, 19(3):333-354.

See Also

RobAStBase-package

Examples

library(RobLox)
ind <- rbinom(100, size=1, prob=0.05) 
x <- rnorm(100, mean=ind*3, sd=(1-ind) + ind*9)
roblox(x)

res <- roblox(x, eps.lower = 0.01, eps.upper = 0.1, returnIC = TRUE)
estimate(res)
confint(res)
confint(res, method = symmetricBias())
pIC(res)
checkIC(pIC(res))
Risks(pIC(res))
Infos(pIC(res))
plot(pIC(res))
infoPlot(pIC(res))

## row-wise application
ind <- rbinom(200, size=1, prob=0.05) 
X <- matrix(rnorm(200, mean=ind*3, sd=(1-ind) + ind*9), nrow = 2)
rowRoblox(X)