Diagnostic Statistical Test 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
- ft:locale
- en-US
- ft:lastEdition
- 2025-04-04
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- ncd1634149624743.ditamap
- dita:ditavalPath
- ruu1634160136230.ditaval
- dita:id
- ncd1634149624743
- TD_BREUSCH_GODFREY
- Checks for the presence of serial correlation among the residual and error terms after running a regression associated with a fitted model.
- TD_BREUSCH_PAGAN_GODFREY
- Checks for heteroscedasticity using one or more variables among the residual terms after running a regression.
- TD_CUMUL_PERIODOGRAM
- Uses the residuals generated during model validation that used the forecasted data points to determine the optimal data model.
- TD_DICKEY_FULLER
- Tests for the presence of one or more unit roots in a series.
- TD_DURBIN_WATSON
- Determines serial correlation between residuals within an independent time series table, or in the tertiary results of an analytical result table (ART).
- TD_FITMETRICS
- Combines the multivariate series with the computed original series mean to generate the goodness-of-fit metrics associated with the modeling exercise.
- TD_GOLDFELD_QUANDT
- Determines if the variance associated with a residual series is homoscedastic or heteroscedastic.
- TD_PORTMAN
- Uses a series of tests to determine the classification of residuals, or if the residuals exhibit homoscedastic variance.
- TD_SELECTION_CRITERIA
- Computes a series of model selection metrics to assist a data scientist in selecting the best model.
- TD_SIGNIF_PERIODICITIES
- Determines if any significant periodicities (seasonal cycles) exist in the residual series.
- TD_SIGNIF_RESIDMEAN
- Determines if the passed-in residual series can be classified as being white noise.
- TD_WHITES_GENERAL
- Checks for the presence of homoscedastic or heteroscedastic variance among the residual terms after running a regression.