Anomaly Detection in High Dimensional and Temporal Data
Overview
This is a modification of 'HDoutliers' package. The 'HDoutliers' algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some limitations that significantly hinder its performance level, under certain circumstances. This package implements the algorithm proposed in Talagala, Hyndman and Smith-Miles (2019) arXiv:1908.04000 for detecting anomalies in high-dimensional data that addresses these limitations of 'HDoutliers' algorithm. We define an anomaly as an observation that deviates markedly from the majority with a large distance gap. An approach based on extreme value theory is used for the anomalous threshold calculation.
Install
Health
NOTERd cross-referencesr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Unknown package ‘HDoutliers’ in Rd xrefs
r-devel-linux-x86_64-fedora-clang
Undeclared package ‘HDoutliers’ in Rd xrefs Unknown package ‘HDoutliers’ in Rd xrefs
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Priyanga Dilini Talagala <pritalagala@gmail.com>’ The Description field contains <arXiv:1908.04000> for detecting anomalies in high-dimensional data Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespace in Imports field not imported from: ‘ks’ All declared Imports should be used.
- NOTE7 OK, 6 NOTENow
- NOTE10 OK, 4 NOTE2026-03-10
Documentation
- Help pages
- 13includes a package overview page
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 50%
- Documented parameters
- 100%
- Return-value docs
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- Help pages citing references
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Checks run against github.com/pridiltal/stray on 2026-10-18.
GitHub Pages site last deployed 2023-11-19
Dependencies
Installing stray adds 28 packages (17 with compiled code, 24 MB of source tarballs). Heaviest: ggplot2 6.0 MB, mclust 2.7 MB, colorspace 2.0 MB.
Code & Tests
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- RR 4.0.0 released · 2020-04-24
- 0.1.02019-12-17
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-12-17
- Total releases
- 2 / 7 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.4.0
- Bundled data
- 202 KB / 8 files
- Download size
- 368 KB
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