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High-Dimensional Covariate-Augmented Overdispersed Poisson Factor Model

1packages depend
3.2Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

A covariate-augmented overdispersed Poisson factor model is proposed to jointly perform a high-dimensional Poisson factor analysis and estimate a large coefficient matrix for overdispersed count data. More details can be referred to Liu et al. (2024) doi:10.1093/biomtc/ujae031.

Install

Health

CRAN checks
13OK
Slowest check: 3.5 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-05-02
  • NOTE11 OK, 1 NOTE2026-04-25
  • OK14 OK2026-04-22
Show 4 earlier changesHide 4 earlier changes
  • ERROR13 OK, 1 ERROR2026-04-18
  • OK14 OK2026-04-16
  • NOTE13 OK, 1 NOTE2026-03-28
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.3
READMEYes · 182 wordsVignettesYes · 1 · dynamicNEWSNoCitation fileNo
Help pages
3
Examples that run
100%3 run in a plain check
Exported functions with examples
100%
Documented parameters
93%
Return-value docs
100%
Help pages citing references
100%
Vignettes (1)

Downloads

3.2K
CRAN downloads in the past year
Rank #12,801 · ~9/day · ~263/mo
Daily download trend is not available in this view yet.
29630 days
88990 days
3.2K1 year
Compare downloads with other packages →
Also on365 r2u3 autocran

Repository

0Stars
0Forks
0Open issues
0Open PRs
0Releases
Last activity 2024-05-02 · The default branch showed an older version (1.2) than CRAN on 2026-10-22
Responsiveness
not measured
PracticesBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/feiyoung/coap on 2026-10-22.

Docs source (1)

GitHub Pages site last deployed 2024-05-02

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)

Installing COAP adds 3 packages (3 with compiled code, 3.2 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB, irlba 375 KB.

Depends (2)
R >= 3.5.0irlba
Imports (3)
MASSstatsRcpp
LinkingTo (2)
Suggests (2)
Enhances (0)
none
Reverse dependencies
1direct
0indirect
Imports 1
Depends, Imports or LinkingTo, most downloaded first

People & History

People (2)
Author, Maintainer since 1.1 (2024)
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
  • 1.3Latest
    record
    2025-03-27 · current release · diff ↗
  • 1.2
    record
    2024-05-02 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • 1.1
    record
    2024-02-29
  • R
    R 4.3.0 released · 2023-04-21

Package metadata

First published
2024-02-29
Total releases
3 / 2 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5.0
Download size
30 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("COAP")
Liu, W., & Zhong, Q. (2025). COAP: High-Dimensional Covariate-Augmented Overdispersed Poisson Factor Model (Version 1.3) [Computer software]. https://doi.org/10.32614/CRAN.package.COAP

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 COAP version 1.3 [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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