R Observatory: Metrics for HRTnomaly version 26.9.19

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

HRTnomaly

26.9.19Package record

Historical, Relational, and Tail Anomaly-Detection Algorithms

0packages depend

2.4Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Luca SartoreCRAN 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. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

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). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

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

Status changes

OK13 OKNow
OK6 OK2026-10-06
WARNING12 OK, 1 WARNING2026-08-21
OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 26.9.19

READMEYes · 572 wordsVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 13includes a package overview page
Examples that run: 92%12 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 15%

How these are measured

Downloads

2.4K

CRAN downloads in the past year

Rank #23,000 · ~6/day · ~197/mo

Releases R versions

Daily download trend is not available in this view yet.

24430 days

56890 days

2.4K1 year

Compare downloads with other packages →

Also on379 r2u7 autocran

How downloads are counted

Dependencies

Declared dependencies

6 external dependencies (excludes base and recommended)

Installing HRTnomaly adds 20 packages (12 with compiled code, 18 MB of source tarballs). Heaviest: stringi 11 MB, vctrs 1.0 MB, dplyr 902 KB.

Depends (1)

R >= 4.5.0

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.

How these are counted

Code & Tests

Datasets

People & History

People (5)

Luca Sartore

Maintainer since 25.2.18 (2025), Author

Author

Author

Author

Author

Listed in earlier versions (1)

Andrew

no longer listed · 25.2.18 to 26.9.19

Releases (4)

Pick two releases to compare their code metrics.

unarchivedReturned to CRAN
2026-10-05
26.9.19Latest
record
2026-10-05 · current release · diff ↗ ·
removed 1 export
pattern:^[[:alpha:]]+

added 10 exports
bayesHRT, bayeswise, bootHRT, cellwise, class_check, dif, fuzzyHRT, gif, pif, setCores
archivedRemoved from CRAN
2026-09-11
issues were not corrected in time
R
R 4.6.0 released · 2026-04-24
25.11.22
record
2025-11-25 · diff ↗
R
R 4.5.0 released · 2025-04-11
25.2.25
record
2025-02-26 · diff ↗
25.2.18
record
2025-02-20
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2025-02-20
Total releases: 4 / 1 yrs
License: AGPL-3 OSI
Minimum R: ≥ 4.5.0
Bundled data: 58 KB / 1 file
Download size: 520 KB

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. (2026). HRTnomaly: Historical, Relational, and Tail Anomaly-Detection Algorithms (Version 26.9.19) [Computer software]. https://doi.org/10.32614/CRAN.package.HRTnomaly

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.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for HRTnomaly version 26.9.19 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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