In this case,
If the simulation is long eough to have passed the transient phase, the output is approximately covariance stationary. That is depends on in the same way as depends on
For a covariance stationary time series s, define the lag k autocovariance by
For k = 0, becomes the population variance
The lag k autocorrelation is the correlation between any two observations
If a time series is covariance stationary, then the calculation of
sample variance can be substantially simplified.
Some discussions about why autocorrelation make it difficult to estimate are skipped