Models
Stochastic process that exhibit long-range dependence are often represented by starting from models that have been devised to be either exactly self similar (a self-similar process), or approximately so. Additional components of dependence can then be added in the same way that short-term dependence models are derived from independence or white noise. Among stochastic models that can be used for long-range dependence behaviour are autoregressive fractionally integrated moving average models, which are defined for discrete-time processes, while continuous-time models might start from fractional Brownian motion.
Read more about this topic: Long-range Dependency
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