Package: ncpen 1.0.0
Dongshin Kim
ncpen: Unified Algorithm for Non-convex Penalized Estimation for Generalized Linear Models
An efficient unified nonconvex penalized estimation algorithm for Gaussian (linear), binomial Logit (logistic), Poisson, multinomial Logit, and Cox proportional hazard regression models. The unified algorithm is implemented based on the convex concave procedure and the algorithm can be applied to most of the existing nonconvex penalties. The algorithm also supports convex penalty: least absolute shrinkage and selection operator (LASSO). Supported nonconvex penalties include smoothly clipped absolute deviation (SCAD), minimax concave penalty (MCP), truncated LASSO penalty (TLP), clipped LASSO (CLASSO), sparse ridge (SRIDGE), modified bridge (MBRIDGE) and modified log (MLOG). For high-dimensional data (data set with many variables), the algorithm selects relevant variables producing a parsimonious regression model. Kim, D., Lee, S. and Kwon, S. (2018) <arxiv:1811.05061>, Lee, S., Kwon, S. and Kim, Y. (2016) <doi:10.1016/j.csda.2015.08.019>, Kwon, S., Lee, S. and Kim, Y. (2015) <doi:10.1016/j.csda.2015.07.001>. (This research is funded by Julian Virtue Professorship from Center for Applied Research at Pepperdine Graziadio Business School and the National Research Foundation of Korea.)
Authors:
ncpen_1.0.0.tar.gz
ncpen_1.0.0.zip(r-4.5)ncpen_1.0.0.zip(r-4.4)ncpen_1.0.0.zip(r-4.3)
ncpen_1.0.0.tgz(r-4.4-x86_64)ncpen_1.0.0.tgz(r-4.4-arm64)ncpen_1.0.0.tgz(r-4.3-x86_64)ncpen_1.0.0.tgz(r-4.3-arm64)
ncpen_1.0.0.tar.gz(r-4.5-noble)ncpen_1.0.0.tar.gz(r-4.4-noble)
ncpen_1.0.0.tgz(r-4.4-emscripten)ncpen_1.0.0.tgz(r-4.3-emscripten)
ncpen.pdf |ncpen.html✨
ncpen/json (API)
# Install 'ncpen' in R: |
install.packages('ncpen', repos = c('https://zeemkr.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/zeemkr/ncpen/issues
binomialclassocoxgaussianhigh-dimensional-datalassolinearmbridgemcpmlogmultinomialnonconvex-penaltiespoissonscadsridgetlp
Last updated 6 years agofrom:e17a0f5f28. Checks:OK: 4 NOTE: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 06 2024 |
R-4.5-win-x86_64 | NOTE | Nov 06 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 06 2024 |
R-4.4-win-x86_64 | NOTE | Nov 06 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 06 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 06 2024 |
R-4.3-win-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-x86_64 | OK | Nov 06 2024 |
R-4.3-mac-aarch64 | OK | Nov 06 2024 |
Exports:coef.cv.ncpencoef.ncpencontrol.ncpencv.ncpencv.ncpen.regexcludedfold.cv.ncpengic.ncpeninteract.datamake.ncpen.datanative_cpp_ncpen_fun_native_cpp_nr_fun_native_cpp_obj_fun_native_cpp_obj_grad_fun_native_cpp_obj_hess_fun_native_cpp_p_ncpen_fun_native_cpp_pen_fun_native_cpp_pen_grad_fun_native_cpp_qlasso_fun_native_cpp_set_dev_mode_ncpenncpen.regplot.cv.ncpenplot.ncpenpower.datapredict.ncpensam.gen.ncpensame.baseto.indicatorsto.ncpen.x.mat
Dependencies:RcppRcppArmadillo