What is Bayesian information criterion in SAP SCM-IBP-DM - Demand?

SAP Term: Bayesian information criterion

• Component: SCM-IBP-DM

• Component Name: Demand

• Description: A calculation method used by the auto-ARIMA algorithm to optimize automatic forecasting.

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• Key Concepts: 
  The Bayesian information criterion (BIC) is a statistical measure used to compare the relative quality of different models. It is used in SAP's Demand Management component of the Supply Chain Management-Integrated Business Planning (SCM-IBP-DM) module to evaluate the accuracy of demand forecasts. The BIC is calculated by taking into account the number of parameters in the model, the number of observations, and the log-likelihood of the data given the model. 
  
  How to use it: 
  The BIC can be used to compare different models and determine which one is best suited for a particular forecasting task. It can also be used to identify potential problems with a model, such as overfitting or underfitting. To use the BIC, first select a set of models that you want to compare. Then, calculate the BIC for each model using the formula provided in SAP's documentation. Finally, compare the BIC values and select the model with the lowest value as your preferred model. 
  
  Tips & Tricks: 
  When using the BIC, it is important to remember that it is only one measure of model accuracy and should not be used as a sole indicator of model performance. Additionally, it is important to consider other factors such as data quality and complexity when selecting a model. 
  
  Related Information: 
  For more information on using the BIC in SAP's Demand Management component, please refer to SAP's documentation on SCM-IBP-DM Demand Management. Additionally, there are many resources available online that provide more detailed information on how to use and interpret the BIC.