ncvreg - Regularization Paths for SCAD and MCP Penalized Regression Models
Fits regularization paths for linear regression, GLM, and Cox regression models using lasso or nonconvex penalties, in particular the minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalty, with options for additional L2 penalties (the "elastic net" idea). Utilities for carrying out cross-validation as well as post-fitting visualization, summarization, inference, and prediction are also provided. For more information, see Breheny and Huang (2011) <doi:10.1214/10-AOAS388> or visit the ncvreg homepage <https://pbreheny.github.io/ncvreg/>.
Last updated 9 days ago
11.88 score 42 stars 39 dependents 458 scripts 4.2k downloadsgrpreg - Regularization Paths for Regression Models with Grouped Covariates
Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bi-level selection methods such as the group exponential lasso, the composite MCP, and the group bridge. For more information, see Breheny and Huang (2009) <doi:10.4310/sii.2009.v2.n3.a10>, Huang, Breheny, and Ma (2012) <doi:10.1214/12-sts392>, Breheny and Huang (2015) <doi:10.1007/s11222-013-9424-2>, and Breheny (2015) <doi:10.1111/biom.12300>, or visit the package homepage <https://pbreheny.github.io/grpreg/>.
Last updated 9 days ago
11.38 score 34 stars 34 dependents 192 scripts 6.0k downloadsvisreg - Visualization of Regression Models
Provides a convenient interface for constructing plots to visualize the fit of regression models arising from a wide variety of models in R ('lm', 'glm', 'coxph', 'rlm', 'gam', 'locfit', 'lmer', 'randomForest', etc.)
Last updated 9 days ago
10.64 score 61 stars 2.4k scripts 4.9k downloadsbiglasso - Extending Lasso Model Fitting to Big Data
Extend lasso and elastic-net model fitting for large data sets that cannot be loaded into memory. Designed to be more memory- and computation-efficient than existing lasso-fitting packages like 'glmnet' and 'ncvreg', thus allowing the user to analyze big data with limited RAM <doi:10.32614/RJ-2021-001>.
Last updated 3 days ago
bigdatalassoout-of-coreparallel-computingcppopenmp
9.80 score 113 stars 1 dependents 74 scripts 1.7k downloads