Title: A General Algorithm to Enhance the Performance of Variable
Selection Methods in Correlated Datasets
Imports: lars, glmnet, igraph, parallel, msgps, Rfast, methods,
Suggests: knitr, rmarkdown, mixOmics, CascadeData
person(given = "Ismail", family= "Aouadi", role = c("ctb"), email = "i.aouadi@unistra.fr"),
Description: An implementation of the selectboost algorithm (Aouadi et al. 2018, <arXiv:1810.01670>), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.

Cascade, graphics, grDevices, varbvs, spls, abind
Description: An implementation of the selectboost algorithm (Bertrand et al. 2020, <arXiv:1810.01670>), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.

Description: An implementation of the selectboost algorithm (Bertrand et al. 2020, 'Bioinformatics', <doi:10.1093/bioinformatics/btaa855>), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.

Suggests: knitr, markdown, rmarkdown, mixOmics, CascadeData

Title: Regularization for variable selection in model-based clustering
Author: Mohammed Sedki, Gilles Celeux, Cathy Maugis-Rabusseau
Description: Regularization for variable selection in model-based clustering and discriminant analysis
Imports: Rcpp (>= 0.11.1), glasso, parallel, Rmixmod