Package: anomaly 4.3.3
Daniel Grose
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>.
Authors:
anomaly_4.3.3.tar.gz
anomaly_4.3.3.tar.gz(r-4.5-noble)anomaly_4.3.3.tar.gz(r-4.4-noble)
anomaly_4.3.3.tgz(r-4.4-emscripten)anomaly_4.3.3.tgz(r-4.3-emscripten)
anomaly.pdf |anomaly.html✨
anomaly/json (API)
NEWS
| # Install 'anomaly' in R: |
| install.packages('anomaly', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- machinetemp - Machine temperature data.
- sim.data - Simulated data.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 29 days agofrom:06f55e32e5. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 20 2024 |
| R-4.5-linux-x86_64 | OK | Aug 20 2024 |
Exports:bardcapacollective_anomaliespassplotpoint_anomaliessamplershowsummary
Dependencies:BHclicolorspacecowplotcpp11dplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6rbibutilsRColorBrewerRcppRdpackrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxtszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Detecting Anomalies in Data | anomaly-package anomaly |
| Detection of multivariate anomalous segments using BARD. | bard |
| A technique for detecting anomalous segments and points based on CAPA. | capa |
| Collective anomaly location, lags, and mean/variance changes. | collective_anomalies collective_anomalies,bard.sampler.class-method collective_anomalies,capa.class-method collective_anomalies,pass.class-method |
| Machine temperature data. | machinetemp |
| Detection of multivariate anomalous segments using PASS. | pass |
| Visualisation of data, collective and point anomalies. | plot,bard.sampler.class plot,bard.sampler.class-method plot,capa.class plot,capa.class-method plot,pass.class plot,pass.class-method |
| Point anomaly location and strength. | point_anomalies point_anomalies,capa.class-method |
| Post processing of BARD results. | sampler |
| Displays S4 objects produced by capa methods. | show show,bard.class-method show,bard.sampler.class-method show,capa.class-method show,pass.class-method |
| Simulated data. | sim.data |
| Summary of collective and point anomalies. | summary summary,bard.class-method summary,bard.sampler.class-method summary,capa.class-method summary,pass.class-method |