fasta: Fast Adaptive Shrinkage/Thresholding Algorithm

A collection of acceleration schemes for proximal gradient methods for estimating penalized regression parameters described in Goldstein, Studer, and Baraniuk (2016) <doi:10.48550/arXiv.1411.3406>. Schemes such as Fast Iterative Shrinkage and Thresholding Algorithm (FISTA) by Beck and Teboulle (2009) <doi:10.1137/080716542> and the adaptive stepsize rule introduced in Wright, Nowak, and Figueiredo (2009) <doi:10.1109/TSP.2009.2016892> are included. You provide the objective function and proximal mappings, and it takes care of the issues like stepsize selection, acceleration, and stopping conditions for you.

Version: 0.1.0
Published: 2018-04-10
Author: Eric C. Chi [aut, cre, trl, cph], Tom Goldstein [aut] (MATLAB original,, Christoph Studer [aut], Richard G. Baraniuk [aut]
Maintainer: Eric C. Chi <ecchi1105 at>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: fasta citation info
CRAN checks: fasta results


Reference manual: fasta.pdf


Package source: fasta_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): fasta_0.1.0.tgz, r-oldrel (arm64): fasta_0.1.0.tgz, r-release (x86_64): fasta_0.1.0.tgz, r-oldrel (x86_64): fasta_0.1.0.tgz


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