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picasso

2.0.1Package record

Sparse Learning with Convex and Concave Penalties

0packages depend
2.9Kdownloads / year
79.7%test coverage
13/13flavors OK

Overview

About
Maintained by Tuo ZhaoCRAN page ↗

Fast regularization paths for sparse Gaussian, binomial, Poisson, square-root-lasso, and multinomial models with lasso, smoothly clipped absolute deviation, or minimax concave penalties. Computation uses pathwise coordinate optimization, active-set updates, warm starts, screening rules, Proximal Newton iterations, quadratic majorization, and adaptive local linear approximation where appropriate. Core solvers are implemented in C++, and coefficient paths are returned as Matrix-compatible objects.

Changes in 2.0.1

Portability

  • Updated the bundled Eigen headers from 3.3.5 to 3.4.0 so the package compiles cleanly under the C++20 default of recent R-devel toolchains (GCC 14/16), removing the -Wdeprecated-enum-enum-conversion install warnings that originated in the older Eigen sources. No package API or numerical behavior changes.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 5.3 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK12 OK2026-04-25
  • NOTE11 OK, 3 NOTE2026-03-25
  • WARNING10 OK, 3 NOTE, 1 WARNING2026-03-18
Show 1 earlier changeHide 1 earlier change
  • NOTE3 OK, 3 NOTE2026-03-10
Advisories

none known

Documentation

In release 2.0.1
READMENoVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 2.0.1Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
22includes a package overview page
Examples that run
100%5 run in a plain check
Exported functions with examples
20%
Documented parameters
98%
Return-value docs
100%
Help pages citing references
9%

Downloads

2.9K
CRAN downloads in the past year
Rank #9,592 · ~8/day · ~240/mo
Daily download trend is not available in this view yet.
38330 days
1K90 days
2.9K1 year
Compare downloads with other packages →
Also on450 r2u3 autocran165 c2d4u

Dependencies

Declared dependencies
1 external dependency (excludes base and recommended)

Installing picasso adds no packages beyond those that come with R.

Depends (2)
R >= 3.1.0Matrix
Imports (1)
methods
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (10)
Author, Maintainer since 1.4.1 (2026)
Author · added in 0.5.4
Author · added in 1.3.0
Author
Author · added in 0.5.4
Author · added in 0.5.0
Contributor · added in 1.4.1
Contributor to bundled Eigen headers
Contributor · added in 1.4.1
Contributor to bundled Eigen headers
Copyright holder · added in 1.4.1
Copyright holders of bundled Eigen headers in src/include/eigen3

Previously maintained by Jason Ge (0.5.4 to 1.3.1) and Xingguo Li (0.1.0 to 0.5.0).

Releases (13)

Pick two releases to compare their code metrics.

  • 2.0.1Latest
    record
    2026-07-25 · current release · diff ↗ ·
    added 12 exports
    print.multinomial, plot.multinomial, coef.multinomial, predict.multinomial, cv.picasso, print.cv.picasso, plot.cv.picasso, coef.cv.picasso, predict.cv.picasso, assess.picasso, print.assess.picasso, confusion.picasso
  • R
    R 4.6.0 released · 2026-04-24
  • 1.5
    record
    2026-03-12 · diff ↗
  • unarchivedReturned to CRAN
    2026-03-10
  • 1.4.1
    record
    first seen 2026-03-10 · diff ↗ ·
    added 1 export
    predict.sqrtlasso
  • R
    R 4.5.0 released · 2025-04-11
  • archivedRemoved from CRAN
    2025-02-09
    issues were not corrected despite reminders
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 1.3.1
    record
    2019-02-21 · diff ↗
  • 1.3.0
    record
    2018-10-03 · diff ↗
  • R
    R 3.5.0 released · 2018-04-23
Show 12 earlier eventsHide 12 earlier events
  • 1.2.0
    record
    2017-12-20 · diff ↗ ·
    added 3 exports
    coef.sqrtlasso, print.sqrtlasso, plot.sqrtlasso
  • 1.0.1
    record
    2017-07-20 · diff ↗
  • R
    R 3.4.0 released · 2017-04-21
  • 0.5.4
    record
    2016-10-06 · diff ↗ ·
    removed 10 exports
    scio.generator, print.lasso, plot.lasso, coef.lasso, predict.lasso, print.scio, plot.scio, scio.plot, print.sim, plot.sim
    added 8 exports
    print.gaussian, plot.gaussian, coef.gaussian, predict.gaussian, print.poisson, plot.poisson, coef.poisson, predict.poisson
  • R
    R 3.3.0 released · 2016-05-03
  • 0.5.0
    record
    2015-12-18 · diff ↗
  • 0.4.7
    record
    2015-09-15 · diff ↗ ·
    removed 1 export
    print.mvr
  • R
    R 3.2.0 released · 2015-04-16
  • 0.3.0
    record
    2014-10-19 · diff ↗
  • 0.2.0
    record
    2014-10-06 · diff ↗ ·
    removed 4 exports
    picasso.lasso, picasso.logit, picasso.mvr, picasso.scio
    added 1 export
    picasso
  • 0.1.0
    record
    2014-08-13
  • R
    R 3.1.0 released · 2014-04-10

Package metadata

First published
2014-08-13
Total releases
13 / 12 yrs
License
GPL-3 OSI
Copyright
See inst/COPYRIGHTS for bundled third-party copyright and license notices.
Minimum R
≥ 3.1.0
Bundled data
176 KB / 2 files
Download size
1.5 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("picasso")
Zhao, T., Ge, J., Guennebaud, G., Jacob, B., Jiang, H., Li, X., Library Authors, E., Liu, H., Wang, M., & Zhang, T. (2026). picasso: Sparse Learning with Convex and Concave Penalties (Version 2.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.picasso

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for picasso version 2.0.1 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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