Analyzing time series data that exhibits seasonal effects
AssigneeHewlett-Packard Development Company, L.P.
InventorJerry Z. Shan
Life of this patent
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Abstract
To analyze a time series of data that exhibits seasonal effects, the time series is processed to obtain a representation in the frequency domain. According to the representation, plural cycle lengths are identified as representing different seasonal effects of the data in the time series, where a first of the plural cycle lengths is greater than a second of the plural cycle lengths.
Claims22
A method executed by a computer to analyze a time series of data that exhibits seasonal effects associated with an enterprise, comprising:
- processing the time series to obtain a representation in a frequency domain;
- and
- according to the representation in the frequency domain, identifying plural cycle lengths as representing different seasonal effects of the data in the time series, wherein a first of the plural cycle lengths is greater than a second of the plural cycle lengths.
A method executed by a computer to analyze a time series of data that exhibits a seasonal effect associated with an enterprise, comprising:
- producing a spectral density of the time series;
- normalizing values in the spectral density with respect to an aggregate of the values of the spectral density at corresponding frequencies to produce a normalized spectral density;
- and
- determining a cycle length corresponding to the seasonal effect based on identifying a peak in the normalized values of the normalized spectral density.
Instructions on a computer-usable medium that when executed cause a computer to:
- process a time series to obtain a representation in a frequency domain;
- and
- according to the representation, identify plural cycle lengths as representing different seasonal effects of data of the time series, wherein the seasonal effects are associated with an enterprise, and wherein a first of the plural cycle lengths is greater than a second of the plural cycle lengths.
Dependencies are inferred from the claim text.