32886: Linear trend model - duke.edu

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If we study the residual plots and diagnostic tests more carefully, we notice that the errors are severely autocorrelated: there are long runs of negative errors alternating with long runs of positive errors. The autocorrelation plot of the errors looks like this: If the model has succeeded in extracting all the "signal" from the data, there should be no pattern at all in the errors: the error in the next period should not be correlated with any previous errors, and the bars on the autocorrelation plot therefore should all be close to the zero line. The linear trend model obviously fails the autocorrelation test in this case.

Linear trend model by duke.edu
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