picasso swMATH ID: 20406 Software Authors: Ge J, Li X, Wang M, Zhang T, Liu H, Zhao Description: R package picasso: Pathwise Calibrated Sparse Shooting Algorithm. Computationally efficient tools for fitting generalized linear model with convex or non-convex penalty. Users can enjoy the superior statistical property of non-convex penalty such as SCAD and MCP which has significantly less estimation error and overfitting compared to convex penalty such as lasso and ridge. Computation is handled by multi-stage convex relaxation and the PathwIse CAlibrated Sparse Shooting algOrithm (PICASSO) which exploits warm start initialization, active set updating, and strong rule for coordinate preselection to boost computation, and attains a linear convergence to a unique sparse local optimum with optimal statistical properties. The computation is memory-optimized using the sparse matrix output. Homepage: https://cran.r-project.org/web/packages/picasso/index.html Source Code: https://github.com/cran/picasso Dependencies: R Related Software: R; biglasso; IsingSampler; MIM; covTest; hglasso; MULAN; glasso; glmnet; sparsenet; camel; flare; huge; NESTA Cited in: 2 Documents all top 5 Cited by 7 Authors 2 Liu, Han 1 Arora, Raman 1 Hong, Mingyi 1 Li, Xingguo 1 Ning, Yang 1 Yang, Zhuoran 1 Zhao, Tuo Cited in 1 Serial 2 Journal of Machine Learning Research (JMLR) Cited in 3 Fields 1 Statistics (62-XX) 1 Computer science (68-XX) 1 Operations research, mathematical programming (90-XX) Citations by Year