A consistent, simple and easy to use set of wrappers around
    the fantastic 'stringi' package. All function and argument names (and
    positions) are consistent, all functions deal with "NA"'s and zero
    length vectors in the same way, and the output from one function is
    easy to feed into the input of another.

covr, htmltools, htmlwidgets, knitr, rmarkdown, testthat (>=
3.0.0)

Hadley Wickham [aut, cre, cph],
  RStudio [cph, fnd]

Provides easy access to, and manipulation of, the Munsell 
    colours. Provides a mapping between Munsell's 
    original notation (e.g. "5R 5/10") and hexadecimal strings suitable 
    for use directly in R graphics. Also provides utilities 
    to explore slices through the Munsell colour tree, to transform 
    Munsell colours and display colour palettes.

Lasso and Elastic-Net Regularized Generalized Linear Models

c(person("Jerome", "Friedman", role=c("aut")),
	     person("Trevor", "Hastie", role=c("aut", "cre"), email = "hastie@stanford.edu"),
	     person("Rob", "Tibshirani", role=c("aut")),
	     person("Balasubramanian", "Narasimhan", role=c("aut")),
	     person("Kenneth","Tay",role=c("aut")),
	     person("Noah", "Simon", role=c("aut")),
	     person("Junyang", "Qian", role=c("ctb")),
	     person("James", "Yang", role=c("aut")))

methods, utils, foreach, shape, survival, Rcpp

Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression, Cox model,  multiple-response Gaussian, and the grouped multinomial regression. There are two new and important additions. The family argument can be a GLM family object, which opens the door to any programmed family. This comes with a modest computational cost, so when the built-in families suffice, they should be used instead.  The other novelty is the relax option, which refits each of the active sets in the path unpenalized. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers listed in the URL below.