anomaly: Detecting Anomalies in Data

Implements Collective And Point Anomaly (CAPA) <arXiv:1806.01947>, Multi-Variate Collective And Point Anomaly (MVCAPA) <arXiv:1909.01691>, Proportion Adaptive Segment Selection (PASS) <doi:10.1093/biomet/ass059>, and Bayesian Abnormal Region Detector (BARD) <doi:10.1214/16-BA998> methods for the detection of anomalies in time series data.

Version: 3.0.1
Depends: R (≥ 3.5.0)
Imports: dplyr, rlang, methods, assertive, Rdpack, ggplot2, reshape2, Rcpp (≥ 0.12.18), robustbase, cowplot
LinkingTo: Rcpp, BH
Suggests: magrittr
Published: 2020-04-06
Author: Alex Fisch [aut], Daniel Grose [aut, cre], Lawrence Bardwell [ctb], Idris Eckley [ths], Paul Fearnhead [ths]
Maintainer: Daniel Grose <dan.grose at lancaster.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
Citation: anomaly citation info
Materials: README
CRAN checks: anomaly results

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Reference manual: anomaly.pdf
Package source: anomaly_3.0.1.tar.gz
Windows binaries: r-devel: anomaly_3.0.1.zip, r-release: anomaly_3.0.1.zip, r-oldrel: anomaly_3.0.1.zip
macOS binaries: r-release: anomaly_3.0.1.tgz, r-oldrel: anomaly_3.0.1.tgz
Old sources: anomaly archive

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