Gaussian Graphical Models with Nonconvex Regularization R package GGMncv version 2.1.2 Estimate Gaussian graphical models with nonconvex penalties, including methods described by Williams (2020) <doi:10.31234/osf.io/ad57p>. Penalties include atan (Wang and Zhu, 2016) <doi:10.1155/2016/6495417>, seamless L0 (Dicker, Huang and Lin, 2013) <doi:10.5705/ss.2011.074>, exponential (Wang, Fan and Zhu, 2018) <doi:10.1007/s10463-016-0588-3>, smooth integration of counting and absolute deviation (Lv and Fan, 2009) <doi:10.1214/09-AOS683>, logarithm (Mazumder, Friedman and Hastie, 2011) <doi:10.1198/jasa.2011.tm09738>, Lq, smoothly clipped absolute deviation (Fan and Li, 2001) <doi:10.1198/016214501753382273>, and minimax concave penalty (Zhang, 2010) <doi:10.1214/09-AOS729>. The package also provides extensions for variable inclusion probabilities, multiple regression coefficients, and statistical inference (Janková and van de Geer, 2015) <doi:10.1214/15-EJS1031>. Software Depends: R (>= 4.0.0) Imports: Rcpp (>= 1.0.4.6), Rdpack (>= 0.11-1), reshape, GGally (>= 1.4.0), ggplot2 (>= 3.3.0), glassoFast (>= 1.0), network (>= 1.15), numDeriv (>= 2016.8-1.1), mathjaxr (>= 1.0-1), MASS (>= 7.3-51.5), methods, parallel, pbapply, sna (>= 2.5), stats, utils LinkingTo: Rcpp, RcppArmadillo Suggests: car, corpcor, corrplot, dplyr, NetworkToolbox, NetworkComparisonTest, nlshrink, rmarkdown, knitr Philippe Rast <rast.ph@gmail.com> Comprehensive R Archive Network (CRAN) Donald Williams [aut], Philippe Rast [cre] GPL-2 2026-05-04 application/tgz https://CRAN.R-project.org/package=GGMncv doi:10.32614/CRAN.package.GGMncv