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oddstream

0.5.0Package record

Outlier Detection in Data Streams

0packages depend
2.7Kdownloads / year
–test coverage
11/13flavors OK

Overview

About

We proposes a framework that provides real time support for early detection of anomalous series within a large collection of streaming time series data. By definition, anomalies are rare in comparison to a system's typical behaviour. We define an anomaly as an observation that is very unlikely given the forecast distribution. The algorithm first forecasts a boundary for the system's typical behaviour using a representative sample of the typical behaviour of the system. An approach based on extreme value theory is used for this boundary prediction process. Then a sliding window is used to test for anomalous series within the newly arrived collection of series. Feature based representation of time series is used as the input to the model. To cope with concept drift, the forecast boundary for the system's typical behaviour is updated periodically. More details regarding the algorithm can be found in Talagala, P. D., Hyndman, R. J., Smith-Miles, K., et al. (2019) doi:10.1080/10618600.2019.1617160.

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespaces in Imports field not imported from:
  ‘RColorBrewer’ ‘graphics’
All declared Imports should be used.

CRAN check page ↗

Slowest check: 2.8 min · r-oldrel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.5.0
README· In the repository, left out of the releaseVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
8 (1 internal)includes a package overview page
Examples that run
40%2 run in a plain check · 3 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
83%
Documented parameters
90%
Return-value docs
100%
Help pages citing references
50%

Downloads

2.7K
CRAN downloads in the past year
Rank #16,222 · ~7/day · ~223/mo
Daily download trend is not available in this view yet.
31130 days
76990 days
2.7K1 year
Compare downloads with other packages →
Also on115 r2u4 autocran

Repository

64Stars
8Forks
2Open issues
0Open PRs
0Releases
146Commits
1Commit identities
146 commits · Last activity 2020-04-02 · Default branch at 0.5.1, ahead of CRAN 0.5.0 (checked 2026-10-22)
Responsiveness
not measured

Stars over time

2024-11-04 · 642026-07-07 · 64
PracticesBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/pridiltal/oddstream on 2026-10-22.

Continuous integration (1)
Travis CI (config file)
Docs source (1)
README.Rmd
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
15 external dependencies (excludes base and recommended)

Installing oddstream adds 44 packages (26 with compiled code, 37 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, mclust 2.7 MB.

Depends (1)
R >= 3.4.0
LinkingTo (0)
none
Suggests (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (3)
Author, Maintainer since 0.5.0 (2019)
Thesis advisor
Thesis advisor
Releases (1)
  • 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
  • R
    R 4.0.0 released · 2020-04-24
  • 0.5.0Latest
    2019-12-16 · current release
  • R
    R 3.6.0 released · 2019-04-26

Package metadata

First published
2019-12-16
Total releases
1 / 7 yrs
License
GPL-3 OSI
Minimum R
≥ 3.4.0
Bundled data
2.3 MB / 2 files
Download size
2.5 MB
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("oddstream")
Talagala, P. D., Hyndman, R. J., & Smith-Miles, K. (2019). oddstream: Outlier Detection in Data Streams (Version 0.5.0) [Computer software]. https://doi.org/10.32614/CRAN.package.oddstream

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 oddstream version 0.5.0 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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