Series Forecasting Functions - Teradata Vantage
Database Unbounded Array Framework Time Series Functions
- Deployment
- VantageCloud
- VantageCore
- Edition
- VMware
- Enterprise
- IntelliFlex
- Product
- Teradata Vantage
- Release Number
- 17.20
- Published
- June 2022
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- en-US
- ft:lastEdition
- 2025-04-04
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- ncd1634149624743
- TD_ARIMAFORECAST
- Combines AR and MA models with differencing to predict future trends or patterns in time series data.
- TD_DTW
- Measures the similarity of two temporal sequences that vary in speed or timing.
- TD_HOLT_WINTERS_FORECASTER
- Uses triple exponential smoothing on a forecast model with seasonal data or double exponential smoothing for non-seasonal data, depending on the parameters.
- TD_MAMEAN
- Forecasts a user-defined number of periods into the future, that is the number of periods beyond the last observed sample point in the series.
- TD_SIMPLEEXP
- Uses simple exponential smoothing for the forecast model for univariate data. It does not use seasonality or trends for the model.