# 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