Analyze ARIMA Residuals

This component analyzes the residuals of an ARIMA (AutoRegressive Integrated Moving Average) model by
1. visualizing auto correlation of the residuals
2. performing Ljung-Box test of autocorrelation at lags 1-10
3. visualizing residuals in a line plot
4. calculating the four first central moments of the residuals
5. performing Jarque-Bera test of normality

Note: This component requires a Python environment with StatsModels package installed. In this blog post we explain how to setup the KNIME Python extension:
https://www.knime.com/blog/setting-up-the-knime-python-extension-revisited-for-python-30-and-20

Required extensions:
KNIME Data Generation
(https://hub.knime.com/knime/extensions/org.knime.features.datageneration/latest)
KNIME Expressions
(https://hub.knime.com/knime/extensions/org.knime.features.expressions/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)
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)

Options

Select column:

Residuals of an ARIMA model to analyze

Number of ARIMA parameters (degrees of freedom):

Degrees of freedom consumed by the ARIMA model depending on the number of parameters (p+d+q) in it. For example, if you have an ARIMA (1,0,1) model, the degrees of freedom 2. This value is needed to perform the Ljung-Box test of stationarity for the residuals.

Nodes

• Column Expressions3 ×
• Breakpoint2 ×
• Color Manager2 ×
• Column Resorter2 ×
• Counter Generation2 ×
• Show all 24 nodes

Extensions

• FeatureKNIME Base nodes
• FeatureKNIME Column Expressions (Labs)
• FeatureKNIME Data Generation
• FeatureKNIME JavaScript Views
• FeatureKNIME Javasnippet
• Show all 9 modules

Links

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