Fast regularization paths for sparse Gaussian, binomial, Poisson, square-root-lasso, and multinomial models with lasso, smoothly clipped absolute deviation, or minimax concave penalties. Computation uses pathwise coordinate optimization, active-set updates, warm starts, screening rules, Proximal Newton iterations, quadratic majorization, and adaptive local linear approximation where appropriate. Core solvers are implemented in C++, and coefficient paths are returned as Matrix-compatible objects.