Detecting Anomalies in Data

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Documentation for package ‘anomaly’ version 4.0.2

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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