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Wavelet-Based Enhanced FDR for Detecting Signals from Complete or Incomplete Spatially Aggregated Data

0packages depend
3.2Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Enhanced False Discovery Rate (EFDR) is a tool to detect anomalies in an image. The image is first transformed into the wavelet domain in order to decorrelate any noise components, following which the coefficients at each resolution are standardised. Statistical tests (in a multiple hypothesis testing setting) are then carried out to find the anomalies. The power of EFDR exceeds that of standard FDR, which would carry out tests on every wavelet coefficient: EFDR choose which wavelets to test based on a criterion described in Shen et al. (2002). The package also provides elementary tools to interpolate spatially irregular data onto a grid of the required size. The work is based on Shen, X., Huang, H.-C., and Cressie, N. 'Nonparametric hypothesis testing for a spatial signal.' Journal of the American Statistical Association 97.460 (2002): 1122-1140.

Install

Health

CRAN checks
13OK
Slowest check: 3.1 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.3
README· In the repository, left out of the releaseVignettesYes · 1 · staticNEWS· In the repository, left out of the releaseCitation fileYes · software entry onlyWebsitenot declared in DESCRIPTION
Help pages
10includes a package overview page
Examples that run
89%8 run in a plain check · 1 hold no code
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
70%

Downloads

3.2K
CRAN downloads in the past year
Rank #11,757 · ~9/day · ~263/mo
Daily download trend is not available in this view yet.
38030 days
91890 days
3.2K1 year
Compare downloads with other packages →
Also on393 r2u4 autocran

Repository

5Stars
1Forks
0Open issues
0Open PRs
4Releases
102Commits
1Commit identities
102 commits · Last activity 2023-08-22
Responsiveness
How these are sampled
PRs merged (all time)
67%
Median days to close, 50 most recently updated closed issues
not measured
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2021-10-17 · 52026-07-07 · 5
PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/andrewzm/efdr on 2026-10-18.

CRAN release process (1)
cran-comments.md
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
16 external dependencies (excludes base and recommended)

Installing EFDR adds 53 packages (34 with compiled code, 57 MB of source tarballs). Heaviest: stringi 11 MB, sf 9.3 MB, sp 4.3 MB.

Depends (1)
R >= 3.5.0
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (2)
Author, Maintainer since 0.1.0 (2014)
Releases (5)

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
  • 1.3Latest
    record
    2023-08-23 · current release · diff ↗
  • 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
  • 1.2
    record
    2021-04-18 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 1.0
    record
    2019-05-20 · diff ↗ ·
    added 1 export
    test.efdr.condsim
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • R
    R 3.3.0 released · 2016-05-03
  • R
    R 3.2.0 released · 2015-04-16
  • 0.1.1
    record
    2015-04-04 · diff ↗
Show 2 earlier eventsHide 2 earlier events
  • 0.1.0
    record
    2015-01-14
  • R
    R 3.1.0 released · 2014-04-10

Package metadata

First published
2015-01-14
Total releases
5 / 11 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.5.0
Download size
922 KB
Appears in task views

Cite

Cite this package

Run in R for the authors' entry:

citation("EFDR")

The package provides a citation file, so citation() returns the authors' own entry.

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 EFDR version 1.3 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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