Autocorrelation Plot

This node will generate both an Autocorrelation Function (ACF) plot and a Partial Auotcorrelation Function (PACF) plot. The ACF plot can be used to visualize correlations between the time series and lagged copies of itself, use this to identify seasonalities in your data. The PACF plot is a modified version of the ACF that attempts to account for and remove serial correlation, use this to identify key lag values to include in (S)ARIMA models.

Options

Value column

The numeric column value to inspect autocorrelations.

Maximum lag

Maximum lag to use when checking for (partial) autocorrelation.

Options

Visualization Parameters

Value Column

The numeric column value to inspect autocorrelations.

Max Lag

Maximum lag to use when checking for (partial) autocorrelation.

Input Ports

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Table containing the numeric column to analyse.

Output Ports

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Table representation of ACF and PACF plots.

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Views

ACF & PACF Plot
Plots for investigating autocorrelations.

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Links

Developers

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