TimeSeries

TimeSeries / TimeSeriesSummary / 0.1.2

README.md

Time Series Summary

Returns various statistics of the given time series.

Input Formats

the algorithm has 2 input formats, a Json input & a standard array input. The output values are the same for all.

Json Input


Uniformly Spaced Input

{
    "uniformData": Double[]
}
{
    "uniformData": [0,1,2,3,4,5]
}

input – input is a 1D array filled with uniformly spaced y coordinates (IE: input[y] where dx(1) = dx(n))

Variably Spaced Input

{
    "dynamicData": Double[][]
}

{
    "dynamicData": [[1,2,3,4,5],[1,2,3,4,5]]
}

input – input is a 2D array where with the first axis X and second Y (IE: input[X][Y])

Standard Array Input


Uniformly Spaced Input

input: Double[]
[1,2,3,4,5,6,7,8,9,10]

input – input is a 1D array filled with uniformly spaced y coordinates (IE: input[y] where dx(1) = dx(n))

Variably Spaced Input

[
    X: Double[], 
    y: Double[]
]

[[1,2,3,4,5,6,7,8,9,10],[2,4,6,8,10,12,14]]

x – X axis of the resultant 2D dataset.

y - Y axis of the resultant 2D dataset.

Output Format

{
  "max": Double,
  "var": Double,
  "geometricMean": Double,
  "populationVariance":Double,
  "slope": Double,
  "kurtosis": Double,
  "min": Double,
  "correlation": Double,
  "intercept": Double,
  "mean": Double,
  "rmse": Double,
  "skewness": Double,
  "standardDeviation": Double
}
  • max – The maximum value of the dataset.
  • min – The minimum value of the dataset.
  • geometricMean – The Geometric Mean of the dataset.
  • populationVariance – The Population Variance of the dataset
  • slope – The slope (y2-y1)/(x2-x1) of the dataset.
  • kurtosis – The Kurtosis of the dataset.
  • correlation – the Correlation between X & Y for the dataset.
  • intercept – The y intercept for the dataset.
  • mean – The average Y value for the dataset.
  • rmse – The Root Mean Square Deviation of the dataset.
  • skewness – The Skewness of the dataset.
  • standardDeviation - The Standard Deviation of the dataset.