0RobLoxBioC-package: Infinitesimally robust estimators for preprocessing omics...

In RobLoxBioC: Infinitesimally Robust Estimators for Preprocessing -Omics Data

Infinitesimally robust estimators for preprocessing omics data

Description

Functions for the determination of optimally robust influence curves and estimators for preprocessing omics data, in particular gene expression data.

Details

Package:	RobLoxBioC
Version:	1.2.1
Date:	2023-05-06
Depends:	R(>= 2.14.0), methods, distr(>= 2.5.2), affy
Imports:	Biobase, BiocGenerics, beadarray, RobLox(>= 0.9.2), distrMod(>= 2.5.2), lattice, RColorBrewer
Suggests:	affydata, hgu95av2cdf, beadarrayExampleData, illuminaHumanv3.db
ByteCompile:	yes
License:	LGPL-3
URL:	https://r-forge.r-project.org/projects/robast/
VCS/SVNRevision:	1214
Encoding:	latin1

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.

Author(s)

Matthias Kohl [e-mail]
Maintainer: Matthias Kohl [e-mail]

References

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

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

M. Kohl, P. Ruckdeschel, and H. Rieder (2010). Infinitesimally Robust Estimation in General Smoothly Parametrized Models. Statistical Methods and Application, 19(3):333-354.

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

Examples

library(RobLoxBioC)

RobLoxBioC documentation built on May 31, 2023, 6:23 p.m.