No autocorrelation refers to the absence of a systematic relationship between the values of a time series at different time points. In the context of modeling, it indicates that residuals from a fitted model are independent of one another, which is crucial for making valid inferences about the parameters and forecasts of ARIMA models. Understanding no autocorrelation helps ensure that the model accurately captures the underlying data patterns without introducing bias.
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