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.

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