TD_PORTMAN

They are executed against the residuals left over after a modeling fit operation and are aimed at determining whether the residuals can be classified as being “white noise” – meaning: zero mean, no evidence of serial correlation amongst the residual/error terms, and the residuals exhibit homoscedastic variance.. All these portmanteau tests treat the residuals as an input series and then use that series as an input to calculate the auto-correlation coefficients or partial auto-correlation coefficients associated with that series. Finally, these coefficients are then used in a subsequent formula to calculate the test statistic value.. The Null Hypothesis associated with all these tests is that the ARIMA model is adequate and that there is no evidence of serial correlation amongst the residuals.

Input ports

1. Type: DB Session
   Teradata Connection
   Connection to a Teradata Database Instance
2. Type: Table
   Input
   This function requires that a series of residuals - left over after running the original regression – be passed into the function. These residuals may either reside within an independent table, or may exist in the form of tertiary results resident within an analytical result table (ART). If the residual series exists as a tertiary result set within an analytical result table, then the caller merely needs to pass in the TABLE_NAME to identify the ART containing the residuals - the DBS software will perform the extraction of the residuals as part of the execution of this function.

Output ports

1. Type: Table
   output of TD_PORTMAN
   output of TD_PORTMAN