Advanced R Programming
BIC, or Bayesian Information Criterion, is a criterion used for model selection that balances model fit with complexity. It helps identify the best model among a set of candidates by penalizing models that are overly complex, thus preventing overfitting. The BIC is particularly useful in time series analysis, like ARIMA and SARIMA models, where finding the right level of complexity is essential for accurate forecasting.
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