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Generate Data (ARIMA)

Synopsis​

This operator generates a time series from an ARIMA process.

Description​

The process is defined by auto-regressive terms and moving-average terms, which defíne how strongly previous values of the time series influence the next values. The result of the operator is a single attribute that includes the time series.

Differentiation​

Generate Data​

This operator also generates a new ExampleSet. It offers many different generating functions and can generate ExampleSets with a label attribute.

Output​

arima​

ExampleSet which has only one attribute that represents the ARIMA time series.

Parameters​

Name of new time series attribute​

This parameter sets the name of the new time series attribute which is returned.

Coefficients of the auto-regressive terms​

This parameter list specifies the coefficients of the auto-regressive terms.

Coefficients of the moving-average terms​

This parameter list specifies the coefficients of the moving-average terms.

Constant​

This parameters sets a starting point for the ARIMA process.

Standard deviation of the innovations​

This parameter sets the standard deviation of the innovations. It controls the amount of variation that is added to each new data point.

Length​

This parameter is the final length of the generated time series. It is the number of examples of the new ExampleSet.

Use local random seed​

This parameter indicates if a local random seed should be used. If selected a local seed is used specifically for this operator.

Local random seed​

If the use local random seed parameter is checked this parameter determines the local random seed.