Functions for the determination of optimally robust influence curves and estimators for preprocessing omics data, in particular gene expression data.
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.
| Package: | RobLoxBioC |
| Version: | 0.9 |
| Date: | 2013-09-12 |
| Depends: | R(>= 2.14.0), methods, Biobase, affy, beadarray, distr, RobLox, lattice, RColorBrewer |
| LazyLoad: | yes |
| ByteCompile: | yes |
| License: | LGPL-3 |
| URL: | http://robast.r-forge.r-project.org/ |
| SVNRevision: | 696 |
| Encoding: | latin1 |
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://www.stamats.de/RRlong.pdf
# NOT RUN {
library(RobLoxBioC)
# }
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