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.


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install.packages("picasso")

1.3.0 by Jason Ge, 5 months ago


Browse source code at https://github.com/cran/picasso


Authors: Jason Ge , Xingguo Li , Haoming Jiang , Mengdi Wang , Tong Zhang , Han Liu and Tuo Zhao


Documentation:   PDF Manual  


Task views: Machine Learning & Statistical Learning


GPL-3 license


Imports methods

Depends on MASS, Matrix


Imported by sparsevar.


See at CRAN