dplyr, glmnet, hexbin, memuse, ModelMetrics, ppcor,

Title: Stepwise Selection for Large Data Sets
Description: 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
Imports: stats, methods, utils, speedglm, bigmemory

Description: Selecting linear and generalized 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.
Imports: stats, methods, utils, RcppEigen, speedglm, bigmemory, R.utils

Imports: stats, methods, utils, RcppEigen, speedglm, bigmemory,

Authors@R: person("Piotr", "Szulc", email = "piotr.michal.szulc@gmail.com", role = c("aut", "cre"))
performed on data which exceed RAM capacity.
Imports: bigmemory, magrittr, matrixStats, methods, R.utils, RcppEigen,

Imports: bigmemory, magrittr, matrixStats, R.utils, RcppEigen,

Title: table-, tapply-, and split-like functionality for matrix and
Maintainer: Mike and Jay <bigmemoryauthors@gmail.com>
Description: This package extends the bigmemory package with table- and
split-like support for big.matrix objects.  The functions may
also be used with regular R matrices for improving speed and
Copyright: (C) 2010 Michael J. Kane and John W. Emerson

Suggests: bigmemory (>= 4.0.0), biganalytics
Description: This package extends the bigmemory package with table-,
tapply-, and split-like support for big.matrix objects.  The
functions may also be used with regular R matrices for

Copyright: (C) 2012 Michael J. Kane and John W. Emerson

Copyright: (C) 2013 Michael J. Kane and John W. Emerson

Author: Michael J. Kane <kaneplusplus@gmail.com> and John W. Emerson <jayemerson@gmail.com>
Description: This package extends the bigmemory package with table- and split-like support for big.matrix objects.  The functions may also be used with regular R matrices for improving speed and memory-efficiency.