Generate Data (ARIMA)
(Time Series)
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 (Data table)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.
Tutorial Processes
Generating a sample ARIMA process
Simple process that generates an ARIMA time series.
