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anomalize  

Tidy Anomaly Detection
View on CRAN: Click here


Download and install anomalize package within the R console
Install from CRAN:
install.packages("anomalize")

Install from Github:
library("remotes")
install_github("cran/anomalize")

Install by package version:
library("remotes")
install_version("anomalize", "0.3.0")



Attach the package and use:
library("anomalize")
Maintained by
Matt Dancho
[Scholar Profile | Author Map]
First Published: 2018-04-06
Latest Update: 2023-10-31
Description:
The 'anomalize' package enables a "tidy" workflow for detecting anomalies in data. The main functions are time_decompose(), anomalize(), and time_recompose(). When combined, it's quite simple to decompose time series, detect anomalies, and create bands separating the "normal" data from the anomalous data at scale (i.e. for multiple time series). Time series decomposition is used to remove trend and seasonal components via the time_decompose() function and methods include seasonal decomposition of time series by Loess ("stl") and seasonal decomposition by piecewise medians ("twitter"). The anomalize() function implements two methods for anomaly detection of residuals including using an inner quartile range ("iqr") and generalized extreme studentized deviation ("gesd"). These methods are based on those used in the 'forecast' package and the Twitter 'AnomalyDetection' package. Refer to the associated functions for specific references for these methods.
How to cite:
Matt Dancho (2018). anomalize: Tidy Anomaly Detection. R package version 0.3.0, https://cran.r-project.org/web/packages/anomalize. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.1.0 (2018-04-06 13:40), 0.1.1 (2018-04-17 13:51), 0.2.0 (2019-09-21 06:10), 0.2.1 (2020-06-19 10:20), 0.2.2 (2020-10-20 20:50), 0.2.3 (2023-02-09 21:10), 0.2.4 (2023-09-26 00:00)
Other packages that cited anomalize R package
View anomalize citation profile
Other R packages that anomalize depends, imports, suggests or enhances
Complete documentation for anomalize
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