Inspect Seasonality

This component calculates autocorrelation with Pearson Correlation for lagged copies of time series. Additionally, it produces an interactive view that displays the Autocorrelation Function (ACF) Plot, Partial Autocorrelation Function (PACF) Plot, and detects the first local maximum of correlation for sign of dominant seasonality.

Required extensions:
KNIME Python Integration
(https://hub.knime.com/knime/extensions/org.knime.features.python2/latest)
KNIME Quick Forms
(https://hub.knime.com/knime/extensions/org.knime.features.js.quickforms/latest)
KNIME JavaScript Views
(https://hub.knime.com/knime/extensions/org.knime.features.js.views/latest)
KNIME Math Expression (JEP)
(https://hub.knime.com/knime/extensions/org.knime.features.ext.jep/latest)

Options

Value Column

Column to apply (P)ACF analysis to. This column has to be a numeric column.

Seasonality Cut Off

The component will only consider correlations above the cut off values as seasonal trends. This value has to be between 0 and 1.

Max Lag

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

Step size of the moving ACF window

Size of steps to move when checking (partial) autocorrelation of different lags. This value should not exceed the value of Max Lag.

Nodes

• Math Formula3 ×
• Integer Configuration2 ×
• Line Plot (JavaScript)2 ×
• Rule-based Row Filter2 ×
• Breakpoint1 ×
• Show all 27 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Column Expressions (Labs)
• FeatureKNIME JavaScript Views
• FeatureKNIME JavaScript Views (Labs)
• FeatureKNIME Javasnippet
• Show all 8 modules

Links

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