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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.
Range: - coefficients_of_the_auto-regressive_terms
This parameter list specifies the coefficients of the auto-regressive terms.
Range: - coefficients_of_the_moving-average_terms
This parameter list specifies the coefficients of the moving-average terms.
Range: - constant
This parameters sets a starting point for the ARIMA process.
Range: - 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.
Range: - length
This parameter is the final length of the generated time series. It is the number of examples of the new ExampleSet.
Range: - 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.
Range: - local_random_seed
If the use local random seed parameter is checked this parameter determines the local random seed.
Range:
Tutorial Processes
Generating a sample ARIMA process
Simple process that generates an ARIMA time series.
