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) <doi:10.1214/16-BA998>. These methods are for the detection of anomalies in time series data. Further information regarding the use of this package along with detailed examples can be found in Fisch, Grose, Eckley, Fearnhead, and Bardwell (2024) <doi:10.18637/jss.v110.i01>.
Version: |
4.3.3 |
Depends: |
R (≥ 3.5.0) |
Imports: |
dplyr, tidyr, methods, ggplot2, Rcpp (≥
0.12.18), xts, zoo, Rdpack, cowplot |
LinkingTo: |
Rcpp, BH |
Suggests: |
robustbase |
Published: |
2024-08-19 |
DOI: |
10.32614/CRAN.package.anomaly |
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 |
Citation: |
anomaly citation info |
Materials: |
NEWS |
CRAN checks: |
anomaly results |
Documentation:
Downloads:
Linking:
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