Authors@R: person("Kisung", "You", role = c("aut", "cre"),
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)

Authors@R: c(person("Kisung", "You", role = c("aut", "cre"),
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>),

Imports: Rcpp, Matrix, Rdpack, stats, doParallel, foreach, parallel

Imports: Rcpp, Matrix, Rdpack, stats, doParallel, foreach, parallel,

Title: Regularized Model with Selecting the Number of Non-Zeros
Author: Xiang Li, Shanghong Xie, Donglin Zeng and Yuanjia Wang
Description: Fit linear and cox models regularized with net (L1 and Laplacian), elastic-net (L1 and L2) or lasso (L1) penalty, and their adaptive forms, such as adaptive lasso and net adjusting for signs of linked coefficients. In addition, it treats the number of non-zero coefficients as another tuning parameter and simultaneously selects with the regularization parameter. The package uses one-step coordinate descent algorithm and runs extremely fast by taking into account the sparsity structure of coefficients.

Title: Penalized Precision Matrix Estimation via ADMM
Authors@R: person("Matt", "Galloway", email = "gall0441@umn.edu",
Description: Estimates a penalized precision matrix via the alternating direction method of multipliers (ADMM) algorithm. It currently supports a general elastic-net penalty that allows for both ridge and lasso-type penalties as special cases. This package is an alternative to the 'glasso' package.
See Boyd et al (2010) <doi:10.1561/2200000016> for details regarding the estimation method.
Imports: stats, parallel, foreach, ggplot2

Imports: stats, parallel, foreach, ggplot2, dplyr
Depends: Rcpp (>= 0.12.10), RcppProgress (>= 0.1), doParallel

Suggests: testthat, knitr, rmarkdown, microbenchmark, pkgdown

Title: Ancient Demographic Modelling Using Radiocarbon
Authors@R: person("Adrian", "Timpson", email = "a.timpson@ucl.ac.uk", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0292-8729"))
Description: Provides tools to directly model underlying population dynamics using date datasets (radiocarbon and other) with a Continuous Piecewise Linear (CPL) model framework, and model comparison framework using BIC. Package also calibrates 14C samples, generates Summed Probability Distributions (SPD), and performs SPD simulation analysis to generate a Goodness-of-fit test for the best selected model.
Author: Adrian Timpson [aut, cre] (<https://orcid.org/0000-0003-0292-8729>)