Fits smoothing spline regression models using scalable algorithms designed for large samples. Five marginal spline types are supported: cubic, different cubic, cubic periodic, cubic thin-plate, and nominal. Random effects and parametric effects are also supported. Response can be Gaussian or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.

Fits smoothing spline regression models using scalable algorithms designed for large samples. Six marginal spline types are supported: cubic, different cubic, cubic periodic, cubic thin-plate, ordinal, and nominal. Random effects and parametric effects are also supported. Response can be Gaussian or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.

Fits smoothing spline regression models using scalable algorithms designed for large samples. Seven marginal spline types are supported: linear, cubic, different cubic, cubic periodic, cubic thin-plate, ordinal, and nominal. Random effects and parametric effects are also supported. Response can be Gaussian or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.

Statistical Tools for Filebacked Big Matrices
Easy-to-use, efficient, flexible and scalable statistical tools.
Package bigstatsr provides and uses Filebacked Big Matrices via memory-mapping.
It provides for instance matrix operations, Principal Component Analysis,
sparse linear supervised models, utility functions and more.
A scientific paper associated with this package is in preparation.
cowplot, doParallel, foreach, ggplot2, glue, graphics,
magrittr, Matrix, methods, parallel, Rcpp, RSpectra, stats
biglasso, bigmemory, covr, glmnet, grid, LiblineaR,
sparseSVM, testthat, viridis
'AUC.R' 'CMSA.R' 'FBM-attach.R' 'crochet.R' 'FBM.R'
'FBM-code256.R' 'FBM-copy.R' 'RcppExports.R' 'SVD.R'
'apply-parallelize.R' 'biglasso.R' 'bigstatsr.R' 'colstats.R'
'counts.R' 'crossprodSelf.R' 'plot.R' 'predict.R' 'randomSVD.R'
'read.R' 'scaling.R' 'sparseSVM.R' 'tcrossprodSelf.R'
'transpose.R' 'univLinReg.R' 'univLogReg.R' 'utils-assert.R'
'utils-mult.R' 'utils.R' 'zzz.R'