RGtk2, gWidgets2, gWidgets2RGtk2, tcltk, Rgraphviz, ssize,
Biobase, impute, limma, grDevices, graphics, methods, stats,
utils
Biostrings, BiocManager, RSQLite, convert, marray, GEOquery,
GEOmetadb, amap, RBGL, WGCNA, KEGGREST, KEGGgraph, cairoDevice,
pdInfoBuilder, lumi, oligo, graph, affy, genefilter,
simpleaffy, beadarray, GOstats, GO.db, globaltest, Category,
annotate
Provides a graphical user interface for analysing DNA microarray data. It performs functional enrichment on genes of interest, identifies gene symbols and also builds co-expression network.

tkrplot, gWidgets2, Rgraphviz, ssize, Biostrings,
BiocManager, RSQLite, GEOquery, GEOmetadb, RBGL, WGCNA,
KEGGREST, KEGGgraph, pdInfoBuilder, lumi, oligo, graph, affy,
genefilter, beadarray, GOstats, GO.db, Category, annotate,
impute, limma, graphics, methods, stats
Provides a comprehensive graphical user interface for analysis of Affymetrix, Agilent, Illumina, Nimblegen and other microarray data. It can perform miscellaneous tasks such as gene set enrichment and test analyses, identifying gene symbols and building co-expression network. It can also estimate sample size for atleast two-fold expression change. The current version is its slenderized form for compatable and flexible implementation.

maRketSim is a market simulator for R.  It was initially designed
around the bond market, with plans to expand to stocks.  maRketSim is
built around the idea of portfolios of fundamental objects.  Therefore
it is slow in its current incarnation, but allows you the flexibility of
seeing exactly what is in your final results, since the objects are retained.

maRketSim is a market simulator for R.  It was initially
designed around the bond market, with plans to expand to
stocks.  maRketSim is built around the idea of portfolios of
fundmantal objects.  Therefore it is slow in its current
incarnation, but allows you the flexibility of seeing exactly
what is in your final results, since the objects are retained.

Mandallaz' model-assisted small area estimators
c(person(given = c("Andreas", "Dominik"), family = "Cullmann",
email = "r-package_masae@arcor.de", role = c("aut","cre"), comment = NULL,
first = NULL, last = NULL)
, person(given = c("Daniel"), family=c("Mandallaz"), role = c("ctb"))
, person(given = c("Alexander", "Francis"), family=c("Massey"), role = c("ctb"))
)
an S4 implementation of the unbiased extension of the model-assisted synthetic-regression estimator proposed by Mandallaz (2013), Mandallaz et al. (2013) and Mandallaz (2014).
It yields smaller variances than the standard bias correction, the generalised regression estimator.
Andreas Dominik Cullmann [aut, cre],
Daniel Mandallaz [ctb],
Alexander Francis Massey [ctb]