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Ergodic versus Stationary

  1. Jun 18, 2012 #1
    Can someone concisely clarify the distinction between an ergodic process and a stationary one? Specifically, can anyone provide examples of processes that are ergodic but not stationary or vice-versa?

    You don't need to provide the definitions; I know what the words mean. But it seems to me that a stationary time series (such as one with the same mean and variance for any sub-interval) would automatically have these same parameters if one took an infinitely long sample of the process, implying ergodicity. What am I missing here?

  2. jcsd
  3. Jun 19, 2012 #2
    Hi Wil,

    I had to check for the definition of ergodic process myself and I got

    So, turns out that you can have stationary processes without mean or variance (e.g. one following a Cauchy distribution), so in this case this process would not be ergodic.

    On the other hand, you might have a process increasing linearly its mean over time, that means that with a sufficiently long sample you can deduce its linear mean behavior and thus fitting the definition of ergodic yet, since the mean is changing overtime, it would not be stationary.
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