bigassertr (>= 0.1.1), bigparallelr (>= 0.2.3), cowplot,
foreach, ggplot2 (>= 3.0), graphics, methods, Rcpp, RSpectra,
stats, tibble, utils
biglasso, bigmemory (>= 4.5.33), bigreadr (>= 0.2), covr,
data.table, glmnet, hexbin, memuse, ModelMetrics, RhpcBLASctl,
spelling (>= 1.2), testthat

biglasso, bigmemory (>= 4.5.33), bigreadr (>= 0.2), covr,
data.table, dplyr, glmnet, hexbin, memuse, ModelMetrics,
RhpcBLASctl, spelling (>= 1.2), testthat
'AUC.R' 'FBM-attach.R' 'crochet.R' 'FBM.R' 'FBM-code256.R'
'FBM-copy.R' 'RcppExports.R' 'SVD.R' 'apply-parallelize.R'
'biglasso.R' 'bigstatsr-package.R' 'colstats.R'
'crossprodSelf.R' 'mult-mat.R' 'mult-vec.R' 'pcor.R' 'plot.R'
'predict.R' 'randomSVD.R' 'read-write.R' 'scaling.R'
'summary.R' 'tcrossprodSelf.R' 'transpose.R' 'univLinReg.R'
'univLogReg.R' 'utils-assert.R' 'utils.R' 'zzz.R'

bigassertr (>= 0.1.1), bigparallelr (>= 0.2.3), cowplot,
foreach, ggplot2 (>= 3.0), graphics, methods, ps (>= 1.4),
Rcpp, RSpectra, stats, tibble, utils
biglasso, bigmemory (>= 4.5.33), bigreadr (>= 0.2), covr,
data.table, dplyr, glmnet, hexbin, memuse, ModelMetrics, ppcor,
RhpcBLASctl, spelling (>= 1.2), testthat

c(
person("Florian", "Privé", email = "florian.prive.21@gmail.com",
role = c("aut", "cre")),
person("Michael", "Blum", role = "ths"),
person("Hugues", "Aschard", email = "hugues.aschard@pasteur.fr", role = "ths"))
bigassertr (>= 0.1.1), bigparallelr (>= 0.2.3), cowplot,
foreach, ggplot2 (>= 3.0), graphics, methods, ps (>= 1.4),
Rcpp, rmio (>= 0.4), RSpectra, stats, tibble, utils
bigmemory (>= 4.5.33), bigreadr (>= 0.2), covr, data.table,
dplyr, glmnet, hexbin, memuse, ModelMetrics, plotly, ppcor,
RhpcBLASctl, spelling (>= 1.2), testthat

bigmemory (>= 4.5.33), bigreadr (>= 0.2), covr, data.table,
dplyr, glmnet, hexbin, memuse, ModelMetrics, ppcor,
RhpcBLASctl, spelling (>= 1.2), testthat

Selecting linear models for large data sets using modified
stepwise procedure and modern selection criteria (like modifications of
Bayesian Information Criterion). Selection can be performed on data which
exceed RAM capacity. Special selection strategy is available, faster than
classical stepwise procedure.
stats, methods, utils, speedglm, bigmemory