Package: GGMncv 2.1.1
GGMncv: Gaussian Graphical Models with Nonconvex Regularization
Estimate Gaussian graphical models with nonconvex penalties <doi:10.31234/osf.io/ad57p>, including the 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 <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>. There are also extensions for computing variable inclusion probabilities, multiple regression coefficients, and statistical inference <doi:10.1214/15-EJS1031>.
Authors:
GGMncv_2.1.1.tar.gz
GGMncv_2.1.1.tar.gz(r-4.5-noble)GGMncv_2.1.1.tar.gz(r-4.4-noble)
GGMncv_2.1.1.tgz(r-4.4-emscripten)GGMncv_2.1.1.tgz(r-4.3-emscripten)
GGMncv.pdf |GGMncv.html✨
GGMncv/json (API)
# Install 'GGMncv' in R: |
install.packages('GGMncv', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/donaldrwilliams/ggmncv/issues
Last updated 3 years agofrom:e78ab7079b. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 28 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 28 2024 |
Exports:boot_eipcompare_edgesconfirm_edgesconstraineddesparsifygen_netget_graphggmncvinferencekl_mvnledoit_wolfmle_known_graphnctpenalty_derivativepenalty_functionscore_binarysignificance_test
Dependencies:clicodacolorspacecpp11crayondplyrfansifarverforcatsgenericsGGallyggplot2ggstatsglassoFastgluegtablehmsisobandlabelinglatticelifecyclemagrittrMASSmathjaxrMatrixmgcvmunsellnetworknlmenumDerivpatchworkpbapplypillarpkgconfigplyrprettyunitsprogresspurrrR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackreshaperlangscalessnastatnet.commonstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Custom Network Comparison Tests
Rendered fromnct_custom.Rmd
usingknitr::rmarkdown
on Nov 28 2024.Last update: 2021-12-14
Started: 2021-12-14
High Dimensional Data: Must Read!!
Rendered fromhigh_dim.Rmd
usingknitr::rmarkdown
on Nov 28 2024.Last update: 2021-12-14
Started: 2021-12-14
NCT: CPU Time
Rendered fromcpu_time.Rmd
usingknitr::rmarkdown
on Nov 28 2024.Last update: 2021-12-14
Started: 2021-12-14
NCT: Null Distributions
Rendered fromnull_dist.Rmd
usingknitr::rmarkdown
on Nov 28 2024.Last update: 2021-12-14
Started: 2021-12-14
Positive Manifold (Sign Restriction)
Rendered fromsign_restrict.Rmd
usingknitr::rmarkdown
on Nov 28 2024.Last update: 2021-12-14
Started: 2021-12-14