SARIMAX Predictor (Labs)

Based on a trained SARIMAX model given at the model input port of this node, the forecast values are computed. This apply node can also be used to update exogenous variable data for forecasting.

Options

Sarimax Forecaster Parameters

SARIMAX Predictor settings to configure the forecasts generated by the input model.

Exogenous Column for Forecasting

Table containing exogenous column for making forecasts on the SARIMAX model, must contain a numeric column with no missing values and of length equal to the number of forecasts to be made.

Reverse Log

Check this box if you applied the log transform inside the SARIMAX Forecaster node while training your model. It will reverse the transform before generating forecasts

Forecast

Forecasts of the given time series h period ahead of the training data.

Generate in-samples dynamically

Check this box to use in-sample prediction as lagged values. Otherwise use true values.

Input Ports

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Trained SARIMAX model.

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Link to exogenous variable

Output Ports

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Forecasted values and their standard errors

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Links

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Installation

To use this node in KNIME, install the extension KNIME Python Extension Development (Labs) from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland
Plugin version: 5.3.3.v202410291554
On NodePit since: 2024-07-09
Last update: 2024-11-20
KNIME versions: Since v5.3

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