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TULIP

1.0.2Package record

A Toolbox for Linear Discriminant Analysis with Penalties

0packages depend
2.3Kdownloads / year
–test coverage
11/13flavors OK

Overview

About

Integrates several popular high-dimensional methods based on Linear Discriminant Analysis (LDA) and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification as mentioned in Yuqing Pan, Qing Mai and Xin Zhang (2019) arXiv:1904.03469. Functions are included for covariate adjustment, model fitting, cross validation and prediction.

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Yuqing Pan <yuqing.pan@stat.fsu.edu>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Yuqing",
                      family = "Pan",
                      role = c("aut", "cre"),
                      email = "yuqing.pan@stat.fsu.edu"),
               person(given = "Qing",
                      family = "Mai",
                      role = "aut",
                      email = "mai@stat.fsu.edu"),
               person(given = "Xin",
                      family = "Zhang",
                      role = "aut",
                      email = "henry@stat.fsu.edu"))
as necessary.

The Description field contains
  (2019) <arXiv:1904.03469>. Functions are included for covariate
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

CRAN check page ↗

Slowest check: 3.6 min · r-devel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.0.2
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
23
Examples that run
100%16 run in a plain check
Exported functions with examples
71%
Documented parameters
99%
Return-value docs
100%
Help pages citing references
87%

Downloads

2.3K
CRAN downloads in the past year
Rank #20,081 · ~6/day · ~195/mo
Daily download trend is not available in this view yet.
23230 days
66490 days
2.3K1 year
Compare downloads with other packages →
Also on335 r2u8 autocran

Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)

Installing TULIP adds 8 packages (3 with compiled code, 7.6 MB of source tarballs). Heaviest: glmnet 2.7 MB, Rcpp 1.8 MB, RcppEigen 1.7 MB.

Depends (1)
R >= 3.1.1
Imports (5)
tensrMatrixMASSglmnetmethods
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (from the free-text Author field) (3)

Maintainer since 1.0 (2019)

Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 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
  • 1.0.2Latest
    record
    2021-01-04 · current release · diff ↗
  • 1.0.1
    record
    2020-06-29 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 1.0
    record
    2019-04-09
  • R
    R 3.5.0 released · 2018-04-23

Package metadata

First published
2019-04-09
Total releases
3 / 7 yrs
License
GPL-2 OSI
Minimum R
≥ 3.1.1
Bundled data
255 KB / 2 files
Download size
292 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("TULIP")

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 TULIP version 1.0.2 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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