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Inspect Seasonality

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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)

Component details

Input ports
  1. Input Table Type: Data
    Data containing selected column for the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) analysis.
Output ports
  1. Data Table of detected local maximum Type: Flow Variable
    This table contains a list of detected local maximum, their corresponding correlation, and lag value.
  2. Flow Variable containing seasonality lag Type: Data
    This flow variable contains the lag value where the dominant seasonality might occur.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.1