R Observatory: Metrics for HRTnomaly version 25.11.22

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

HRTnomaly

25.11.22

Historical, Relational, and Tail Anomaly-Detection Algorithms

0packages depend

2.3Kdownloads / year

–test coverage

13/13checks pass

Overview

About

Maintained by Luca SartoreFirst published 2025-02-203 releasesCRAN page ↗

The presence of outliers in a dataset can substantially bias the results of statistical analyses. To correct for outliers, micro edits are manually performed on all records. A set of constraints and decision rules is typically used to aid the editing process. However, straightforward decision rules might overlook anomalies arising from disruption of linear relationships. Computationally efficient methods are provided to identify historical, tail, and relational anomalies at the data-entry level (Sartore et al., 2024; doi:10.6339/24-JDS1136). A score statistic is developed for each anomaly type, using a distribution-free approach motivated by the Bienaymé-Chebyshev's inequality, and fuzzy logic is used to detect cellwise outliers resulting from different types of anomalies. Each data entry is individually scored and individual scores are combined into a final score to determine anomalous entries. In contrast to fuzzy logic, Bayesian bootstrap and a Bayesian test based on empirical likelihoods are also provided as studied by Sartore et al. (2024; doi:10.3390/stats7040073). These algorithms allow for a more nuanced approach to outlier detection, as it can identify outliers at data-entry level which are not obviously distinct from the rest of the data. --- This research was supported in part by the U.S. Department of Agriculture, National Agriculture Statistics Service. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA, or US Government determination or policy.

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("HRTnomaly", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-hrtnomaly

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-HRTnomaly

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-HRTnomaly

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 2.5 min · r-devel-windows-x86_64

Code health

None

Tests · ratio 0.00

not tracked

Coverage

3

Dependencies · direct

Check history

OK2026-08-05
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 572 wordsVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 46%
Documented parameters: not tracked
Return-value docs: not tracked
References docs: 15%

Downloads

2.3K

CRAN downloads in the past year

Rank #17,660 · ~6/day · ~190/mo

Releases R versions

Daily download trend is not available in this view yet.

16130 days

61090 days

2.3K1 year

Compare downloads with other packages →

Also on413 r2u23 autocran

Dependencies

Declared dependencies

6 external dependencies (excludes base and recommended)

Depends (1)

R >= 4.0.0

Imports (3)

dplyr purrr tidyr

LinkingTo (0)

none

Suggests (3)

knitr rmarkdown cellWise

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (6)

Maintainer (1)

Luca Sartore

Maintainer

Authors (5)

Author

Author

Author

Author

Author

Listed in earlier versions (1)

Andrew

no longer listed · 25.2.18 to 25.11.22

Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
25.11.22Latest
2025-11-25 · current release · diff ↗
R
R 4.5.0 released · 2025-04-11
25.2.25
2025-02-26 · diff ↗
25.2.18
2025-02-20
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2025-02-20
Total releases: 3 / 1 yrs
License: AGPL-3 OSI
Minimum R: ≥ 4.0.0
Bundled data: 58 KB / 1 file
Download size: 510 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Anomaly Detection

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("HRTnomaly")

Format

Sartore, L., Bejleri, V., Chen, L., Dau, A., Sartore, L., & van Wart, J. (2025). HRTnomaly: Historical, Relational, and Tail Anomaly-Detection Algorithms (Version 25.11.22) [Computer software]. https://doi.org/10.32614/CRAN.package.HRTnomaly

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

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

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for HRTnomaly version 25.11.22 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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