search for: jasa_mfh_fin

...coordinate descent, using a penalized least-squares framework and a non-convex penalty. The package is based on our JASA paper Rahul Mazumder, Jerome Friedman and Trevor Hastie: SparseNet : Coordinate Descent with Non-Convex Penalties. (JASA 2011) http://www.stanford.edu/~hastie/Papers/Sparsenet/jasa_MFH_final.pdf We use Zhang's MC+ penalty to impose sparsity in model selection. This penalty parametrizes a family ranging between L1 and L0 regularization. One nice feature of this family is that the single-coordinate optimization problems are convex, making it ideal for coordinate descent. The pa...

...coordinate descent, using a penalized least-squares framework and a non-convex penalty. The package is based on our JASA paper Rahul Mazumder, Jerome Friedman and Trevor Hastie: SparseNet : Coordinate Descent with Non-Convex Penalties. (JASA 2011) http://www.stanford.edu/~hastie/Papers/Sparsenet/jasa_MFH_final.pdf We use Zhang's MC+ penalty to impose sparsity in model selection. This penalty parametrizes a family ranging between L1 and L0 regularization. One nice feature of this family is that the single-coordinate optimization problems are convex, making it ideal for coordinate descent. The pa...