The quasi-akaike information criterion (QAIC) is a statistical tool used for model selection, particularly when dealing with models based on quasi-likelihood estimation. It provides a way to compare different models by balancing their goodness of fit against their complexity, helping to identify the model that best explains the data without overfitting.
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