TD_ARIMAESTIMATE Function | Teradata Vantage - TD_ARIMAESTIMATE - Teradata Vantage

Database Unbounded Array Framework Time Series Functions

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Vantage
Release Number
17.20
Published
June 2022
Language
English (United States)
Last Update
2024-10-04
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TD_ARIMAESTIMATE estimates the coefficients corresponding to an ARIMA (AutoRegressive Integrated Moving Average) model, and to fit a series with an existing ARIMA model. The function can also provide the "goodness of fit" and the residuals of the fitting operation. The function generates model layer used as input for the TD_ARIMAVALIDATE and TD_ARIMAFORECAST functions. This function is for univariate series.

TD_ARIMAESTIMATE takes one or two inputs, the second input is optional. The first input is a time series. The second input references the model context. When only one input is passed in, TD_ARIMAESTIMATE operates in a coefficient estimate mode. When two inputs are passed in, TD_ARIMAESTIMATE operates in a model apply mode. When the second input is passed in, you must include an INPUT_FMT(MODE()) clause.

You can use the FIT_PERCENTAGE parameter to pass a portion of the data, such as 80%, to the TD_ARIMAESTIMATE function. The ART produced includes the ARTVALDATA layer which contains the remaining 20%, and can be used with TD_ARIMAVALIDATE for the validation exercise.

The following statistical functions are typically run after TD_ARIMAESTIMATE to determine if the residuals are zero mean, have no serial correlation, contain no cycles (periodicities) or exhibit homoscedastic variance:
  • TD_BREUSCH_GODFREY, serial correlation test
  • TD_DURBIN_WATSON, serial correlation test
  • TD_BREUSCH_PAGAN_GODFREY, heteroscedastic variance test
  • TD_WHITES_GENERAL, heteroscedastic variance test
  • TD_GOLDFED_QUANDT, heteroscedastic variance test
The following procedure is an example of how to use TD_ARIMAESTIMATE:
  1. Run the TD_ARIMAESTIMATE function to estimate the coefficients for the ARIMA model.
  2. [Optional] Run TD_ARIMAVALIDATE function to validate the ARIMA model, when FIT_PERCENTAGE was not set to 100 percent in TD_ARIMAESTIMATE.
  3. Run the TD_ARIMAFORECAST function with input from step 1 (FIT_PERCENTAGE was set to 100 percent) or step 2 to (FIT_PERCENTAGE was set to a value less than 100 percent).