Collate: Cascade-package.R global.R micro_array.R network.R

person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy-bertrand@utt.fr", comment = c(ORCID = "0000-0002-4615-1512")),

Title: Experimental Data of Cascade Experiments in Genomics
Description: These experimental expression data (5 leukemic 'CLL' B-lymphocyte of aggressive form from 'GSE39411', <doi:10.1073/pnas.1211130110>), after B-cell receptor stimulation, are used as examples by packages such as the 'Cascade' one, a modeling tool allowing gene selection, reverse engineering, and prediction in cascade networks. Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M. (2014) <doi:10.1093/bioinformatics/btt705>.

Author: Dr. Simon Mueller <simon.mueller@muon-stat.com>, PD Dr. Juergen Dippon <juergen.dippon@mathematik.uni-stuttgart.de>
Maintainer: Dr. Simon Mueller <simon.mueller@muon-stat.com>
Description: Given a large set of problems and their individual solutions case based reasoning seeks to solve a new problem by referring to the solution of that problem which is "most similar" to the new problem. Crucial in case based reasoning is the decision which problem "most closely" matches a given new problem. The basic idea is to define a family of distance functions and to use these distance functions as parameters of local averaging regression estimates of the final result. Then that distance function is chosen for which the resulting estimate is optimal with respect to a certain error measure used in regression estimation. The idea is based on: Dippon J. et al. (2002) <DOI:10.1016/S0167-9473(02)00058-0>.
Imports: R6, ranger, survival, tidyverse, cowplot, dplyr, data.table,
Suggests: testthat, knitr, rmarkdown, RcppArmadillo

Title: Datasetsfor Categorical Data Analysis by Agresti
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>
Description: Datasets used in the book "Categorical Data Analysis"
by Agresti (2012, ISBN:978-0-470-46363-5) but not printed in the book.
Datasets and help pages were automatically produced from the source
<http://www.stat.ufl.edu/~aa/cda/data.html> by the R script foo.R,
which can be found in the GitHub repository.