Autocorrelation Function

See: Function, AFC, Autocorrelation Analysis, Autocorrelation Coefficient, Partial Autocorrelation Function.

References

http://en.wikipedia.org/wiki/Autocorrelation#Statistics
- QUOTE: In statistics, the autocorrelation of a random process describes the correlation between values of the process at different points in time, as an function of the two times or of the time difference. Let X be some repeatable process, and i be some point in time after the start of that process. (i may be an integer for a discrete-time process or a real number for a continuous-time process.) Then Xi is the value (or realization) produced by a given run of the process at time i. Suppose that the process is further known to have defined values for mean μ_i and variance σ_i² for all times i. Then the definition of the autocorrelation between times s and t is: [math]\displaystyle{ R(s,t) = \frac{\operatorname{E}[(X_t - \mu_t)(X_s - \mu_s)]}{\sigma_t\sigma_s}\,, }[/math] where "E" is the expected value operator. …
  … When the autocorrelation function is normalized by mean and variance, it is sometimes referred to as the 'autocorrelation coefficient.