High-dimensional sparse regression in R: penalized Huber, SVM, quantile, and Wilcoxon rank regression via the finite smoothing algorithm. Fast C++ (Rcpp) coordinate-descent kernels with elastic-net penalties, cross-validation, and SCAD/MCP non-convex penalties.
r rcpp cpp machinelearning support-vector-machines quantile-regression huber-loss-regression high-dimensional-optimization elastic-net-regularization statstistics rank-regression
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Updated
Jun 11, 2026 - R