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 alocal random seedshould be used. If selected a local seed is used specifically for this operator.

Local random seed

If theuse local random seedparameter is checked this parameter determines the local random seed.