How To Fix /SAPAPO/AMON_LIST073 - MLR: R**2 > Durbin Watson

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/AMON_LIST -

• Message number: 073

• Message text: MLR: R**2 > Durbin Watson

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message /SAPAPO/AMON_LIST073 - MLR: R**2 > Durbin Watson ?

  The SAP error message /SAPAPO/AMON_LIST073 MLR: R**2 > Durbin Watson typically occurs in the context of the Advanced Planning and Optimization (APO) module, particularly when dealing with statistical analysis in demand planning or forecasting.
  Cause:
  This error indicates that the R-squared value (R²) of a regression model is greater than the Durbin-Watson statistic. In regression analysis, R² measures the proportion of variance in the dependent variable that can be explained by the independent variables. The Durbin-Watson statistic tests for the presence of autocorrelation in the residuals from a regression analysis. 
  When R² is greater than the Durbin-Watson statistic, it suggests that the model may be overfitting the data or that there are issues with the residuals, such as autocorrelation, which can lead to unreliable statistical inferences.
  Solution:
  To resolve this issue, consider the following steps:
  
  
  Check Model Specification: Ensure that the model is correctly specified. This includes verifying that the right independent variables are included and that the functional form of the model is appropriate.
  
  
  Examine Residuals: Analyze the residuals of the regression model. Look for patterns that might indicate autocorrelation. You can use plots or statistical tests (like the Breusch-Godfrey test) to check for autocorrelation.
  
  
  Adjust the Model: If autocorrelation is present, consider adjusting the model. This might involve:
  
  Adding lagged variables.
  Using a different modeling approach (e.g., ARIMA models for time series data).
  Reducing the number of independent variables to avoid overfitting.
  
  
  
  Re-evaluate Data: Check the data for outliers or anomalies that could be affecting the regression results. Cleaning the data may help improve the model's performance.
  
  
  Consult Documentation: Review SAP documentation or notes related to the specific version of APO you are using, as there may be known issues or patches available.
  
  
  Seek Expert Help: If the problem persists, consider consulting with a data analyst or a statistician who has experience with regression analysis and SAP APO.
  
  
  Related Information:
  
  Durbin-Watson Statistic: A value between 0 and 4, where a value around 2 indicates no autocorrelation. Values below 1 or above 3 suggest positive or negative autocorrelation, respectively.
  R-squared Value: Ranges from 0 to 1, with higher values indicating a better fit of the model to the data.
  Statistical Software: If you are using statistical software or tools within SAP, ensure they are configured correctly for the analysis you are performing.
  
  By following these steps, you should be able to address the error and improve the reliability of your regression analysis in SAP APO.