AI LAYER

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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