Title: An Amazing Fast Way to Fit Elastic Net
Authors@R: c(person("Jingyi","Ma",email = "jingyima@163.com", role = c("aut")),
person("Qiuhong","Lai",email = "lailaqiuhong@gmail.com", role = "ctb"),
person("Linyu","Zuo",email = "zuozhe5959@gmail.com", role = c("ctb","cre")),
person("Yi","Yang",email = "lucious.stat.y@gmail.com", role = "ctb"),
person("Meng","Su",email = "SUmeng97@126.com", role = "ctb"),
person("Zhen","Yu", email = "amy.yuzhen@foxmail.com", role = 'ctb'),
person("Gege","Gao", email = "gaogege1995@163.com", role = 'ctb'),
person("Xiao","Liu", email = "lucinecoco@163.com", role = 'ctb'),
person("Xueni","Ruan", email = "ruanxueni96@163.com", role = 'ctb'),
person("Xinyuan","Yang", email = "yangxinyuan100@126.com", role = 'ctb'),
person("Yu","Bai", email = "yukisunflower@sina.com", role = 'ctb'),
person("Zhijun","Liao", email = "econzhijun@163.com", role = 'ctb')
Description: 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.

Title: Raster Image Processing and Vector Recognition
Description: If there is a need to recognise edges on a raster image or a bitmap or any kind of a matrix, one can find packages
that does only 90 degrees vectorization. Typically the nature of artefact images is linear and can be vectorized in much more
efficient way than draw a series of 90 degrees lines. The fasteraster package does recognition of lines using only one pass.

Title: Raster Images Processing and Vector Recognition

It also allows to calculate mass and the mass centers for the recognized zones or polygons.

Title: Fast Polygon to Raster Conversion
person("Michael", "Sumner", role = "ctb",
Description: Provides a drop-in replacement for rasterize() from the 'raster'
package that takes 'sf'-type 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
Suggests: testthat, microbenchmark, knitr, rmarkdown, sf
Author: Noam Ross [aut, cre] (<https://orcid.org/0000-0002-1642-628X>),