anomaly: Detecting Anomalies in Data

Implements Collective And Point Anomaly (CAPA) Fisch, Eckley, and Fearnhead (2022) <doi:10.1002/sam.11586>, Multi-Variate Collective And Point Anomaly (MVCAPA) Fisch, Eckley, and Fearnhead (2021) <doi:10.1080/10618600.2021.1987257>, Proportion Adaptive Segment Selection (PASS) Jeng, Cai, and Li (2012) <doi:10.1093/biomet/ass059>, and Bayesian Abnormal Region Detector (BARD) Bardwell and Fearnhead (2015) <arXiv:1412.5565>. These methods are for the detection of anomalies in time series data.

Version: 4.3.2
Depends: R (≥ 3.5.0)
Imports: dplyr, tidyr, methods, ggplot2, Rcpp (≥ 0.12.18), xts, zoo, Rdpack, cowplot
LinkingTo: Rcpp, BH
Suggests: robustbase
Published: 2023-11-23
Author: Alex Fisch [aut], Daniel Grose [aut, cre], Lawrence Bardwell [aut, ctb], Idris Eckley [aut, ths], Paul Fearnhead [aut, ths]
Maintainer: Daniel Grose <dan.grose at lancaster.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: anomaly results

Documentation:

Reference manual: anomaly.pdf

Downloads:

Package source: anomaly_4.3.2.tar.gz
Windows binaries: r-devel: anomaly_4.3.2.zip, r-release: anomaly_4.3.2.zip, r-oldrel: anomaly_4.3.2.zip
macOS binaries: r-release (arm64): anomaly_4.3.2.tgz, r-oldrel (arm64): anomaly_4.3.2.tgz, r-release (x86_64): anomaly_4.3.2.tgz
Old sources: anomaly archive

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