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Functions for Time Series Analysis

Below functions are used for series data analysis.

seriesOutliersDetectTukey​

Detects outliers in series data using Tukey Fences.

Syntax

Arguments

  • series - An array of numeric values.
  • min_percentile - The minimum percentile to be used to calculate inter-quantile range (IQR). The value must be in range [0.02,0.98]. The default is 0.25.
  • max_percentile - The maximum percentile to be used to calculate inter-quantile range (IQR). The value must be in range [0.02,0.98]. The default is 0.75.
  • K - Non-negative constant value to detect mild or stronger outliers. The default value is 1.5.

At least four data points are required in series to detect outliers.

Returned value

  • Returns an array of the same length as the input array where each value represents score of possible anomaly of corresponding element in the series. A non-zero score indicates a possible anomaly. Array.

Examples

Query:

Result:

Query:

Result:

seriesPeriodDetectFFT​

Finds the period of the given series data using FFT - Fast Fourier transform

Syntax

Arguments

  • series - An array of numeric values

Returned value

  • A real value equal to the period of series data. NaN when number of data points are less than four. Float64.

Examples

Query:

Result:

Result:

seriesDecomposeSTL​

Decomposes a series data using STL (Seasonal-Trend Decomposition Procedure Based on Loess) into a season, a trend and a residual component.

Syntax

Arguments

  • series - An array of numeric values
  • period - A positive integer

The number of data points in series should be at least twice the value of period.

Returned value

  • An array of four arrays where the first array include seasonal components, the second array - trend, the third array - residue component, and the fourth array - baseline(seasonal + trend) component. Array.

Examples

Query:

Result: