A Simple Non-Stationary Mean Ergodic Theorem, with Bonus Weak Law of Large Numbers
This brief pedagogical note re-proves a simple theorem on the convergence, in $L_2$ and in probability, of time averages of non-stationary time series to the mean of expectation values. The basic condition is that the sum of covariances grows sub-quadratically with the length of the time series. I m...
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Sprache: | eng |
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Zusammenfassung: | This brief pedagogical note re-proves a simple theorem on the convergence, in
$L_2$ and in probability, of time averages of non-stationary time series to the
mean of expectation values. The basic condition is that the sum of covariances
grows sub-quadratically with the length of the time series. I make no claim to
originality; the result is widely, but unevenly, spread bit of folklore among
users of applied probability. The goal of this note is merely to even out that
distribution. |
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DOI: | 10.48550/arxiv.2203.09085 |