Detecting Anomalies in Data

---

Documentation for package ‘anomaly’ version 4.0.2

• DESCRIPTION file.

Help Pages

ac_corrected	Transforms the data X to account for autocorrelation.
bard	Detection of multivariate anomalous segments using BARD.
capa	A technique for detecting anomalous segments and points based on CAPA.
capa.mv	Detection of multivariate anomalous segments and points using MVCAPA.
capa.uv	Detection of univariate anomalous segments and points using CAPA.
collective_anomalies	Collective anomaly location, lags, and mean/variance changes.
collective_anomalies-method	Collective anomaly location, lags, and mean/variance changes.
Lightcurves	Kepler Lightcurve data.
machinetemp	Machine temperature data.
moving_ac_corrected	Transforms the data X to account for autocorrelation using a moving window and a burn-in.
pass	Detection of multivariate anomalous segments using PASS.
period_average	A function to search the Kepler data for periodically recurring dips in luminosity.
plot	Visualisation of data, collective and point anomalies.
plot-bard.sampler.class	Visualisation of data, collective and point anomalies.
plot-method	Visualisation of data, collective and point anomalies.
plot-pass.class	Visualisation of data, collective and point anomalies.
point_anomalies	Point anomaly location and strength.
point_anomalies-method	Point anomaly location and strength.
robustscale	robustscale
sampler	Post processing of BARD results.
scapa.mv	Online detection of multivariate anomalous segments and points using SMVCAPA.
scapa.uv	Detection of univariate anomalous segments using SCAPA.
show	Displays S4 objects produced by capa methods.
show-method	Displays S4 objects produced by capa methods.
simulate	A function for generating simulated multivariate data
summary	Summary of collective and point anomalies.
summary-method	Summary of collective and point anomalies.
tierney	tierney