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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "picasso" in publications use:'
type: software
license: GPL-3.0-only
title: 'picasso: Pathwise Calibrated Sparse Shooting Algorithm'
version: 1.3.1
doi: 10.32614/CRAN.package.picasso
abstract: 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.
authors:
- family-names: Ge
  given-names: Jason
  email: jiange@princeton.edu
- family-names: Li
  given-names: Xingguo
- family-names: Jiang
  given-names: Haoming
- family-names: Wang
  given-names: Mengdi
- family-names: Zhang
  given-names: Tong
- family-names: Liu
  given-names: Han
- family-names: Zhao
  given-names: Tuo
repository: https://cranhaven.r-universe.dev
commit: 4e65629e4b620d1bf8ae195153487901b3389c80
date-released: '2019-02-10'
contact:
- family-names: Ge
  given-names: Jason
  email: jiange@princeton.edu