For ordinal rating data, consider the accelerated EM algorithm to estimate and test models within the family of
    CUB models (where CUB stands for Combination of a 
	discrete Uniform and a shifted Binomial distributions). The procedure is built upon Louis' identity for the observed information matrix. Best-subset variable selection is then implemented since it becomes more feasible from the computational point of view.

Provides an R interface to Bob Jenkin's streaming, 
 non-cryptographic 'SpookyHash' hash algorithm for use in digest-based 
 comparisons of R objects. 'fastdigest' plugs directly into R's internal 
 serialization machinery, allowing digests of all R objects the serialize() 
 function supports, including reference-style objects via custom hooks. Speed is
 high and scales linearly by object size; memory usage is constant and 
 negligible.

Creates dummy columns from columns that have categorical variables (character or factor types). You can also specify which columns to make dummies out of, or which columns to ignore. Also creates dummy rows from character, factor, and Date columns. This package provides a significant speed increase from creating dummy variables through model.matrix().

Fit Elastic Net, Lasso, and Ridge regression and do cross-validation in a fast way. We build the algorithm based on Least Angle Regression by Bradley Efron, Trevor Hastie, Iain Johnstone, etc. (2004)(<doi:10.1214/009053604000000067 >) and some algorithms like Givens rotation and Forward/Back Substitution. In this way, many matrices to be computed are retained as triangular matrices which can eventually speed up the computation. The fitting algorithm for Elastic Net is written in C++ using Armadillo linear algebra library.

Provides a drop-in replacement for rasterize() from the 'raster'
   package that takes polygon vector or data frame objects, and is much faster. 
   There is support for the main options provided by the rasterize() function, 
   including setting the field used and background value, and options for 
   aggregating multi-layer rasters. Uses the scan line algorithm attributed to
   Wylie et al. (1967) <doi:10.1145/1465611.1465619>.