Lasso and Elastic-Net Regularized Generalized Linear Models (glmnet)
Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.
Sparse and Dense Matrix Classes and Methods (Matrix)
Classes and methods for dense and sparse matrices and operations on them using ‘LAPACK’ and ‘SuiteSparse’.
Memory management in R by delayed assignments (SOAR)
Allows objects to be stored on disc and automatically recalled into memory, as required, by delayed assignment.