• gamsel

  • Referenced in 22 articles [sw19132]
  • Generalized Additive Models. Using overlap grouped lasso penalties, gamsel selects whether a term...
  • grplasso

  • Referenced in 13 articles [sw08193]
  • Fitting user specified models with Group Lasso penalty. Fits user specified (GLM-) models with Group ... Lasso penalty...
  • msgl

  • Referenced in 17 articles [sw26552]
  • Multinomial logistic regression with sparse group lasso penalty. Simultaneous feature selection and parameter estimation ... classes. The algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel...
  • ConstrainedLasso

  • Referenced in 13 articles [sw42315]
  • constrained lasso extends the widely used lasso to handle linear constraints, which allow the user ... show that, for an arbitrary penalty matrix, the generalized lasso can be transformed...
  • BigVAR

  • Referenced in 4 articles [sw31349]
  • VARX models with structured Lasso Penalties...
  • ConvexLAR

  • Referenced in 3 articles [sw16543]
  • loss function with lasso or group lasso penalty. Variable selection in recurrent event and panel...
  • cqrReg

  • Referenced in 3 articles [sw21332]
  • both with and without an adaptive lasso penalty for variable selection. In this paper...
  • ipflasso

  • Referenced in 5 articles [sw31364]
  • package ipflasso: Integrative Lasso with Penalty Factors. The core of the package is cvr2.ipflasso...
  • cvplogistic

  • Referenced in 5 articles [sw29394]
  • considered in this implementation. For the MCP penalty, the package also provides the local linear ... package also provides a Lasso-concave hybrid penalty for fast variable selection. The hybrid penalty ... applies the concave penalty only to the variables selected by the Lasso...
  • APPLE

  • Referenced in 4 articles [sw13354]
  • Penalized Likelihood Estimators. Both convex penalties (such as LASSO) and folded concave penalties (such...
  • flare

  • Referenced in 21 articles [sw12406]
  • also provide the extension of these Lasso variants to sparse Gaussian graphical model estimation including ... CLIME using either L1 or adaptive penalty. Missing values can be tolerated for Dantzig selector...
  • FLLat

  • Referenced in 2 articles [sw19127]
  • through an application of the fused lasso penalty to each feature. Some simulation analyses show...
  • ordPens

  • Referenced in 6 articles [sw08178]
  • independent variables using a group lasso or generalized ridge penalty...
  • aispu

  • Referenced in 1 article [sw36076]
  • aiSPU) test based on the truncated Lasso penalty and an adaptive testing idea, which ... aiSPU) test based on the truncated Lasso penalty and an adaptive testing idea. Some related...
  • MHTrajectoryR

  • Referenced in 3 articles [sw18786]
  • regressions have been used with a Lasso type penalty to perform the detection of associations...
  • rqPen

  • Referenced in 7 articles [sw19266]
  • quantile regression for LASSO, SCAD and MCP functions including group penalties. Provides a function that...
  • hierband

  • Referenced in 1 article [sw31337]
  • banding procedure (using a hierarchical group lasso penalty) for covariance estimation that is introduced...
  • crrp

  • Referenced in 2 articles [sw28755]
  • variable selection for the PSH model. Penalties include LASSO, SCAD, MCP, and their group versions...
  • picasso

  • Referenced in 3 articles [sw20406]
  • overfitting compared to convex penalty such as lasso and ridge. Computation is handled by multi...
  • JGL

  • Referenced in 2 articles [sw27159]
  • Estimation on Multiple Classes. The Joint Graphical Lasso is a generalized method for estimating Gaussian ... solve JGL under two penalty functions: The Fused Graphical Lasso (FGL), which employs a fused ... penalty to encourage inverse covariance matrices to be similar across classes, and the Group Graphical ... Lasso (GGL), which encourages similar network structure between classes. FGL is recommended over...