Interview Question: AIC

Sample Question #212 (statistics)

What’s the Akaike Information Criterion (AIC)? Why is it a useful concept?

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One Response to Interview Question: AIC

  1. Brett says:

    The AIC is an alternative measure of goodness of fit for a regression. Its definition can be expressed several ways; following Tsay, the general form of AIC is:
      AIC = -2/N * ln(likehood) + 2/N * K
    where K is the number of parameters and N the number of observations.
    The AIC is useful because 1) it allows us to evaluate whether a regression is the right fit, and 2) more interestingly, in time series, it helps us determine the order of an AR process.

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