Outlier Detection in Data Streams
Overview
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.
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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.
- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- 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%
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People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.5.0Latest2019-12-16 · current release
- RR 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
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