BIC, or Bayesian Information Criterion, is a statistical tool used for model selection among a finite set of models. It estimates the quality of each model while penalizing for the number of parameters to avoid overfitting. A lower BIC value suggests a better-fitting model, making it essential for comparing different statistical models and determining the most appropriate one based on the data.
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