Time series anomaly detection using multiple statistical models

Details Time series anomaly detection using multiple statistical models Time series anomaly detection using multiple statistical models

2007-12-18

2007-12-18

Raymond, Edward (Department: 2857)

Data processing: measuring, calibrating, or testing

Measurement system

Statistical measurement

C703S022000

Reexamination Certificate

active

11560312

ABSTRACT:
A time series is analyzed by multiple functions simultaneously to identify an anomaly for a data point in the series. Data point values are predicted by the multiple functions. An anomaly occurs when an actual data point in the series differs significantly from the data point's predicted value as generated by the functions. If enough statistical models detect an anomaly has occurred for a data point, an anomaly event is generated. The set of functions can include different types of functions, the same function type configured with different constants, or a combination of these.

REFERENCES:
patent: 2007/0088534 (2007-04-01), MacArthur et al.

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